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2017 Vol. 39, No. 5
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2017, 39(5): 1017-1023.
doi: 10.11999/JEIT161040
Abstract:
In order to effectively improve radar detection ability of moving target under the conditions of strong clutter and complex motion characteristics, the principle framework of Short-Time sparse Time-Frequency Distribution (ST-TFD) is established combing the advantages of TFD-based moving target detection and sparse representation. Then, Short-Time Sparse Fourier Transform (ST-SFT) and Short-Time Sparse FRactional Fourier transform (ST-SFRFT)-based radar moving target detection methods are proposed and applied to micro-Doppler signature extraction and detection of marine target. It is verified by real radar data that the proposed methods can achieve high-resolution and low complexity TFD of time-varying signal in time-sparse domain, and has the advantages of high efficiency, good time-frequency resolution, anti-clutter, and so on. It can be expected that the proposed methods can provide a novel solution for radar clutter suppression and moving target detection.
In order to effectively improve radar detection ability of moving target under the conditions of strong clutter and complex motion characteristics, the principle framework of Short-Time sparse Time-Frequency Distribution (ST-TFD) is established combing the advantages of TFD-based moving target detection and sparse representation. Then, Short-Time Sparse Fourier Transform (ST-SFT) and Short-Time Sparse FRactional Fourier transform (ST-SFRFT)-based radar moving target detection methods are proposed and applied to micro-Doppler signature extraction and detection of marine target. It is verified by real radar data that the proposed methods can achieve high-resolution and low complexity TFD of time-varying signal in time-sparse domain, and has the advantages of high efficiency, good time-frequency resolution, anti-clutter, and so on. It can be expected that the proposed methods can provide a novel solution for radar clutter suppression and moving target detection.
2017, 39(5): 1024-1029.
doi: 10.11999/JEIT160763
Abstract:
For airborne dual-antenna FMCW InSAR systems, the time-varying baseline can be considerably high due to its low flight height, atmospheric turbulence, location and attitude errors and low accuracy of MEMS IMU, seriously affecting the DEM accuracy. To deal with this problem, a time-varying baseline estimation method for FMCW InSAR system is proposed. Firstly, the time-varying baseline derivative for each range gate using single look complex image data is established, and the space-variant model in range direction is established. Then the horizontal and vertical time-varying baseline derivative obtained using random sample consistent method is integrated. Finally, the proposed method is implemented on real experimental FMCW InSAR data, the effectiveness of proposed method is validated by comparing estimated results with high accuracy POS information.
For airborne dual-antenna FMCW InSAR systems, the time-varying baseline can be considerably high due to its low flight height, atmospheric turbulence, location and attitude errors and low accuracy of MEMS IMU, seriously affecting the DEM accuracy. To deal with this problem, a time-varying baseline estimation method for FMCW InSAR system is proposed. Firstly, the time-varying baseline derivative for each range gate using single look complex image data is established, and the space-variant model in range direction is established. Then the horizontal and vertical time-varying baseline derivative obtained using random sample consistent method is integrated. Finally, the proposed method is implemented on real experimental FMCW InSAR data, the effectiveness of proposed method is validated by comparing estimated results with high accuracy POS information.
2017, 39(5): 1030-1035.
doi: 10.11999/JEIT160684
Abstract:
In the application of millimeter-wave Linear Frequency Modulated Continuous Wave (LFMCW) radar for water surface detection, the echo of water surface itself is always covered by the echo of stationary targets and noises, leading to the result that water surface texture can hardly be seen in the figures obtained by the conventional imaging algorithm. To solve this problem, an imaging algorithm of millimeter-wave LFMCW radar for water surface texture is proposed, the Dechirp technique is adopted to complete the range compression in range direction, and the data is divided into blocks to be dealt with separately in azimuth direction. During the processing in azimuth direction, interference from static targets is removed in frequency domain according to the fact that stationary targets and moving targets have different Doppler frequencies; then, based on the electromagnetic scattering characteristic of water surface, a maximum likelihood estimation method is used to estimate azimuth spectrum parameters to calculate the energy of water surface echo. The proposed algorithm is used to process measured data, and the results show that water surface texture can be obtained, which means that the proposed algorithm is superior to the traditional one.
In the application of millimeter-wave Linear Frequency Modulated Continuous Wave (LFMCW) radar for water surface detection, the echo of water surface itself is always covered by the echo of stationary targets and noises, leading to the result that water surface texture can hardly be seen in the figures obtained by the conventional imaging algorithm. To solve this problem, an imaging algorithm of millimeter-wave LFMCW radar for water surface texture is proposed, the Dechirp technique is adopted to complete the range compression in range direction, and the data is divided into blocks to be dealt with separately in azimuth direction. During the processing in azimuth direction, interference from static targets is removed in frequency domain according to the fact that stationary targets and moving targets have different Doppler frequencies; then, based on the electromagnetic scattering characteristic of water surface, a maximum likelihood estimation method is used to estimate azimuth spectrum parameters to calculate the energy of water surface echo. The proposed algorithm is used to process measured data, and the results show that water surface texture can be obtained, which means that the proposed algorithm is superior to the traditional one.
2017, 39(5): 1036-1043.
doi: 10.11999/JEIT160747
Abstract:
The conventional statistical Space-Time Adaptive Processing (STAP) methods, such as sample selection and sample weighting methods, and so forth, have a very low utilization ratio of sample data, which results in that the problem of training samples lack is more prominent in heterogeneous clutter environment. Thus, in this paper, the space-time spectrum of the clutter Cell Under Test (CUT) is estimated according to the distribution characteristics of the clutter and the moving target in the range and space-time two dimensional spectrum plane. In addition, the median filtering is exploited to avoid the disturbance due to the moving target for the estimation of clutter spectrum. Finally, the reconstruction of clutter covariance matrix without sacrificing space-time aperture and clutter suppression is achieved．The results of the simulated experiments demonstrate that the proposed method can effectively alleviate the STAP performance degradation due to the interference target, discrete terrain clutter or isolation interference, compared with the traditional statistical STAP methods.
The conventional statistical Space-Time Adaptive Processing (STAP) methods, such as sample selection and sample weighting methods, and so forth, have a very low utilization ratio of sample data, which results in that the problem of training samples lack is more prominent in heterogeneous clutter environment. Thus, in this paper, the space-time spectrum of the clutter Cell Under Test (CUT) is estimated according to the distribution characteristics of the clutter and the moving target in the range and space-time two dimensional spectrum plane. In addition, the median filtering is exploited to avoid the disturbance due to the moving target for the estimation of clutter spectrum. Finally, the reconstruction of clutter covariance matrix without sacrificing space-time aperture and clutter suppression is achieved．The results of the simulated experiments demonstrate that the proposed method can effectively alleviate the STAP performance degradation due to the interference target, discrete terrain clutter or isolation interference, compared with the traditional statistical STAP methods.
2017, 39(5): 1044-1050.
doi: 10.11999/JEIT160796
Abstract:
The steady reference signal reconstruction is one of the key technologies of passive radar with digital waveform, and the accuracy of channel estimation is directly related to the reference signal purity. To deal with the problem of reference signal reconstruction for Digital Terrestrial Multimedia Broadcasting (DTMB) based passive radar when the receiving system samples at a non-integer multiples of the symbol rate, an improved channel estimation is proposed on the basis of matching pursuit algorithm which is based on the compression perception. Simulation results show that compared to the widely used time domain correlation algorithm and the Least Squares (LS) algorithm, the improved algorithm has better frequency adaptability and robustness, and performs superiorly in various channel environments. Real data processing results further demonstrate that it significantly raises the quality of the reconstructed signal using the proposed algorithm and provides a better condition for the target detection.
The steady reference signal reconstruction is one of the key technologies of passive radar with digital waveform, and the accuracy of channel estimation is directly related to the reference signal purity. To deal with the problem of reference signal reconstruction for Digital Terrestrial Multimedia Broadcasting (DTMB) based passive radar when the receiving system samples at a non-integer multiples of the symbol rate, an improved channel estimation is proposed on the basis of matching pursuit algorithm which is based on the compression perception. Simulation results show that compared to the widely used time domain correlation algorithm and the Least Squares (LS) algorithm, the improved algorithm has better frequency adaptability and robustness, and performs superiorly in various channel environments. Real data processing results further demonstrate that it significantly raises the quality of the reconstructed signal using the proposed algorithm and provides a better condition for the target detection.
2017, 39(5): 1051-1057.
doi: 10.11999/JEIT160774
Abstract:
The inversion of topography and tree height in forest area is one of the most important applications in the Polarimetric SAR Interferometry (PolInSAR). In this paper, the coherent region of the PolInSAR data is modeled and the best normal matrix is used to approximate the cross correlation matrix, further, the whitened interferometric cross-correlation matrix is obtained. The coherence region of the whitened interferometric cross-correlation matrix is a straight line. Two arbitrary coherences obtained under two different polarization states can be applied to fitting a straight line. Based on the fitting line, the topographical phase can be estimated successfully. Referring to the relationship between the volume scattering and the tree height, look-up table method is used to search the correct tree height. The proposed method can avoid the complex steps of the traditional method, which needs to solve all the coherences under different polarization states to obtain the edge of the coherent region. The proposed method simplifies the inversion procedure and improves the efficiency of inversion, meanwhile, achieves the correct topography as well as the tree height. Finally, the simulation data are applied to validating the validity and reliability of the proposed method.
The inversion of topography and tree height in forest area is one of the most important applications in the Polarimetric SAR Interferometry (PolInSAR). In this paper, the coherent region of the PolInSAR data is modeled and the best normal matrix is used to approximate the cross correlation matrix, further, the whitened interferometric cross-correlation matrix is obtained. The coherence region of the whitened interferometric cross-correlation matrix is a straight line. Two arbitrary coherences obtained under two different polarization states can be applied to fitting a straight line. Based on the fitting line, the topographical phase can be estimated successfully. Referring to the relationship between the volume scattering and the tree height, look-up table method is used to search the correct tree height. The proposed method can avoid the complex steps of the traditional method, which needs to solve all the coherences under different polarization states to obtain the edge of the coherent region. The proposed method simplifies the inversion procedure and improves the efficiency of inversion, meanwhile, achieves the correct topography as well as the tree height. Finally, the simulation data are applied to validating the validity and reliability of the proposed method.
2017, 39(5): 1058-1063.
doi: 10.11999/JEIT160846
Abstract:
The application of conformal sparse array to airship-borne passive radar is studied, and the target detection performance of airship-borne passive radar is analyzed. Because of the importance of antenna in radar system, embattle method of sparse array Digital Beam Forming (DBF) antenna and antenna pattern index are selectively analyzed. Layout of airship-borne sparse array is implemented based on the combination of Barker code. In order to obtain ideal DBF antenna pattern, a method of compensating the curve array to the linear array is proposed. With respect to the possible deformation problem, the distributed Position and Orientation System (POS) is used to measure the deformation error based on which curve fitting is implemented to conduct accurate compensation. Simulation results show the effectiveness of the proposed method.
The application of conformal sparse array to airship-borne passive radar is studied, and the target detection performance of airship-borne passive radar is analyzed. Because of the importance of antenna in radar system, embattle method of sparse array Digital Beam Forming (DBF) antenna and antenna pattern index are selectively analyzed. Layout of airship-borne sparse array is implemented based on the combination of Barker code. In order to obtain ideal DBF antenna pattern, a method of compensating the curve array to the linear array is proposed. With respect to the possible deformation problem, the distributed Position and Orientation System (POS) is used to measure the deformation error based on which curve fitting is implemented to conduct accurate compensation. Simulation results show the effectiveness of the proposed method.
2017, 39(5): 1064-1070.
doi: 10.11999/JEIT160870
Abstract:
Sentinel-1 satellite constellation offers enough Synthetic Aperture Radar (SAR) images for long-term water monitoring, due to its relative large swath, great revisit frequency and high resolution. The middle and upper Yangtze River suffers serious flood disaster in 2016. It is significant to detect water and its changes of Poyang Lake, since it is one of the important flood storage lakes along the Yangtze River mainstream. However, the traditional segmentation algorithm has shortage in edge preservation and the accuracy of water detection, especially in the case of Poyang Lake, which is widely distributed and has more complex background, weak edges and blurred edges. A new Active Contour Model (ACM) algorithm based on local narrowband is proposed to solve these problems, and it is applied to Sentinel-1A observations related to Poyang Lake. First, a cascade two-level Otsu approach is adopted to obtain the initial contour. Second, the local narrowband is built along the initial contour to reduce the calculating time. Finally, a region-based ACM is introduced into the local narrowband to stop the contours at weak or blurred edges. Experiment results show that the new method has advantages in the edge preservation and obtains better segmentation results with respect to other methods.
Sentinel-1 satellite constellation offers enough Synthetic Aperture Radar (SAR) images for long-term water monitoring, due to its relative large swath, great revisit frequency and high resolution. The middle and upper Yangtze River suffers serious flood disaster in 2016. It is significant to detect water and its changes of Poyang Lake, since it is one of the important flood storage lakes along the Yangtze River mainstream. However, the traditional segmentation algorithm has shortage in edge preservation and the accuracy of water detection, especially in the case of Poyang Lake, which is widely distributed and has more complex background, weak edges and blurred edges. A new Active Contour Model (ACM) algorithm based on local narrowband is proposed to solve these problems, and it is applied to Sentinel-1A observations related to Poyang Lake. First, a cascade two-level Otsu approach is adopted to obtain the initial contour. Second, the local narrowband is built along the initial contour to reduce the calculating time. Finally, a region-based ACM is introduced into the local narrowband to stop the contours at weak or blurred edges. Experiment results show that the new method has advantages in the edge preservation and obtains better segmentation results with respect to other methods.
2017, 39(5): 1071-1078.
doi: 10.11999/JEIT160798
Abstract:
This paper proposes a supervised image segmentation algorithm for high resolution remote sensing images by introducing the Gaussian Mixture Model (GMM) with spatial relationship in order to solve the problem of the increasing dissimilarity in the same object and the decreasing of dissimilarity between two different objects. The proposed algorithm takes samples according to the segmentation areas and uses the least squared method to fit the histogram. GMMs are established to describe the complex spectral characteristic in each area accurately. Then spatial relationships are taken consider into the probability measures in GMMs to make the dissimilarities of pixels in a window is determined by all the pixels in the same window. Overall the GMMs can describe the spatial relationships between the pixels in high resolution remote sensing images. Finally the segmentation result is obtained by maximum probability principle. To verify the feasibility and the effectively of the proposed algorithm, the algorithm is performed on real high resolution remote sensing and synthetic images and compared the results with that of FCM and HMRF-FCM based segmentation algorithm. Qualitative and quantitative results prove that the proposed algorithm could improve the accuracy of segmentation.
This paper proposes a supervised image segmentation algorithm for high resolution remote sensing images by introducing the Gaussian Mixture Model (GMM) with spatial relationship in order to solve the problem of the increasing dissimilarity in the same object and the decreasing of dissimilarity between two different objects. The proposed algorithm takes samples according to the segmentation areas and uses the least squared method to fit the histogram. GMMs are established to describe the complex spectral characteristic in each area accurately. Then spatial relationships are taken consider into the probability measures in GMMs to make the dissimilarities of pixels in a window is determined by all the pixels in the same window. Overall the GMMs can describe the spatial relationships between the pixels in high resolution remote sensing images. Finally the segmentation result is obtained by maximum probability principle. To verify the feasibility and the effectively of the proposed algorithm, the algorithm is performed on real high resolution remote sensing and synthetic images and compared the results with that of FCM and HMRF-FCM based segmentation algorithm. Qualitative and quantitative results prove that the proposed algorithm could improve the accuracy of segmentation.
2017, 39(5): 1079-1087.
doi: 10.11999/JEIT160762
Abstract:
In visual tracking, the efficient and robust feature representation is the key factor to solve the problem of tracking drift in complex environments. Therefore, to solve the problems of the complex and time-consuming of the pre-training process of deep neural network and the drift of the single network tracking, an online tracking method based on an adaptive deep sparse network is proposed under the tracking structure of particle filter. A deep sparse neural network architecture, which can be adaptively selected according to different types of targets, is constructed with the implementation of the Rectifier Linear Unit (ReLU) activation function. The robustness of deep tracking network can be easily achieved only through the online training of limited labeled samples. The results of experiments show that, compared with the state-of-the-art tracking algorithm, the average success ratio and precision of the proposed algorithm are both the highest, and they are raised by 20.64% and 17.72% respectively contrasted with the Deep Learning Tracker (DLT) algorithm based on deep learning. The proposed method can solve the problems of tracking drift efficiently, and shows better robustness, especially for the complex environment such as illumination changes, background clutter and so on.
In visual tracking, the efficient and robust feature representation is the key factor to solve the problem of tracking drift in complex environments. Therefore, to solve the problems of the complex and time-consuming of the pre-training process of deep neural network and the drift of the single network tracking, an online tracking method based on an adaptive deep sparse network is proposed under the tracking structure of particle filter. A deep sparse neural network architecture, which can be adaptively selected according to different types of targets, is constructed with the implementation of the Rectifier Linear Unit (ReLU) activation function. The robustness of deep tracking network can be easily achieved only through the online training of limited labeled samples. The results of experiments show that, compared with the state-of-the-art tracking algorithm, the average success ratio and precision of the proposed algorithm are both the highest, and they are raised by 20.64% and 17.72% respectively contrasted with the Deep Learning Tracker (DLT) algorithm based on deep learning. The proposed method can solve the problems of tracking drift efficiently, and shows better robustness, especially for the complex environment such as illumination changes, background clutter and so on.
2017, 39(5): 1088-1095.
doi: 10.11999/JEIT160730
Abstract:
For moving hand segmentation, in order not to use unreasonable assumptions and to solve the hand-face occlusion, a segmentation method based on skin color, grayscale, depth and motion cues is proposed. Firstly, according to the variance information of grayscale and depth optical flow, Motion Region of Interest (MRoI) is adaptively extracted to locate the moving body part. Then, corners which satisfy skin color and adaptive motion constraints are detected as skin seed points in the MRoI. Next, skin seed points are grown to [JL1]obtain candidate hand region utilizing skin color, depth and motion criterions. Finally, edge depth gradient, skeleton extraction and optimal path search are employed to segment moving hand region from candidate hand region. Experiment results show that the proposed method can effectively and accurately segment moving hand region under different circumstances, especially when the face is occluded by the hand.
For moving hand segmentation, in order not to use unreasonable assumptions and to solve the hand-face occlusion, a segmentation method based on skin color, grayscale, depth and motion cues is proposed. Firstly, according to the variance information of grayscale and depth optical flow, Motion Region of Interest (MRoI) is adaptively extracted to locate the moving body part. Then, corners which satisfy skin color and adaptive motion constraints are detected as skin seed points in the MRoI. Next, skin seed points are grown to [JL1]obtain candidate hand region utilizing skin color, depth and motion criterions. Finally, edge depth gradient, skeleton extraction and optimal path search are employed to segment moving hand region from candidate hand region. Experiment results show that the proposed method can effectively and accurately segment moving hand region under different circumstances, especially when the face is occluded by the hand.
2017, 39(5): 1096-1100.
doi: 10.11999/JEIT160765
Abstract:
To detect the sea ice in small-scale fixed sea area, a shore-based sea ice detecting method is developed using GNSS reflected signal. Firstly, the method needs to calculate the intensity ratio of GNSS satellite reflected signal and direct signal, which is the ratio of the reflected signal correlation power and the direct signal correlation power. Then the sea ice thickness is obtained based on the empirical model. Preliminary analysis of the GNSS reflected signal collected during the sea ice experiment can obtain sea ice thickness which is 10~20 cm and shows good agreement between the GNSS-R sea ice thickness.
To detect the sea ice in small-scale fixed sea area, a shore-based sea ice detecting method is developed using GNSS reflected signal. Firstly, the method needs to calculate the intensity ratio of GNSS satellite reflected signal and direct signal, which is the ratio of the reflected signal correlation power and the direct signal correlation power. Then the sea ice thickness is obtained based on the empirical model. Preliminary analysis of the GNSS reflected signal collected during the sea ice experiment can obtain sea ice thickness which is 10~20 cm and shows good agreement between the GNSS-R sea ice thickness.
2017, 39(5): 1101-1108.
doi: 10.11999/JEIT160663
Abstract:
Spectral Domain Optical Coherence Tomography (SD-OCT) imaging technique is widely used in the diagnosis of ophthalmology diseases. The segmentation of retinal layers plays a very important role in the diagnosis of glaucoma. In this paper, a random forest classifier is used which is trained by twelve different features to find the boundaries between layers. Whats more, the relative gray feature and the neighbor features are used to solve the problem of large errors under the condition of uneven illumination. In the last, the segmentation results of the proposed algorithm, a traditional algorithm and Iowa segmentation software on ten sets of retinal images are compared with manual segmentation, and the average absolute boundary errors are 9.202.57m, 11.332.99m, 10.273.01m, respectively. The experiments show that the proposed algorithm can segment the Retinal Never Fiber Layer (RNFL) better.
Spectral Domain Optical Coherence Tomography (SD-OCT) imaging technique is widely used in the diagnosis of ophthalmology diseases. The segmentation of retinal layers plays a very important role in the diagnosis of glaucoma. In this paper, a random forest classifier is used which is trained by twelve different features to find the boundaries between layers. Whats more, the relative gray feature and the neighbor features are used to solve the problem of large errors under the condition of uneven illumination. In the last, the segmentation results of the proposed algorithm, a traditional algorithm and Iowa segmentation software on ten sets of retinal images are compared with manual segmentation, and the average absolute boundary errors are 9.202.57m, 11.332.99m, 10.273.01m, respectively. The experiments show that the proposed algorithm can segment the Retinal Never Fiber Layer (RNFL) better.
2017, 39(5): 1109-1115.
doi: 10.11999/JEIT160657
Abstract:
In actual applications, noises may inevitably exist, and thus to study the denoising method for images is great significant task in image processing filed that attracts much attention in recent years. In this paper, based on the statistical property of Meridian distributed and the Total Variational (TV), a total variational method is proposed for restoring images degraded by alpha-stable noise. Besides, in order to obtain a strictly convex model, a quadratic penalty term is added, which guarantees the uniqueness of the solution. For solving the novel convex variational model, a primal-dual algorithm is employed to solve the above model, and the convergence of the algorithm is proved. The experimental results demonstrate that the feasibility and effectiveness of the proposed model for the noisy images with alpha-stable noise.
In actual applications, noises may inevitably exist, and thus to study the denoising method for images is great significant task in image processing filed that attracts much attention in recent years. In this paper, based on the statistical property of Meridian distributed and the Total Variational (TV), a total variational method is proposed for restoring images degraded by alpha-stable noise. Besides, in order to obtain a strictly convex model, a quadratic penalty term is added, which guarantees the uniqueness of the solution. For solving the novel convex variational model, a primal-dual algorithm is employed to solve the above model, and the convergence of the algorithm is proved. The experimental results demonstrate that the feasibility and effectiveness of the proposed model for the noisy images with alpha-stable noise.
2017, 39(5): 1116-1122.
doi: 10.11999/JEIT160712
Abstract:
As an important part in the security and protection system of cities, smart monitoring cameras which are equipped with intelligent video analytics ability can monitor in different scenes and pre-alarm abnormal behaviors or events. Nevertheless, with the growing number of smart monitoring cameras, the challenges to analytics, storage and retrieval of massive surveillance video data need to be solved in the big data era. This paper proposes an intelligent processing method which makes full use of smart cameras to big surveillance video data. The method consists of three parts: the intelligent pre-alarming for abnormal events, smart storage for surveillance video and rapid retrieval for evidence videos, which aim to improve the utilization efficiency of surveillance video data. Experimental results prove that the proposed approach can reliably pre-alarm abnormal events, efficiently reduce storage space of recorded video and significantly improve the evidence video retrieval rates associated with specific suspects.
As an important part in the security and protection system of cities, smart monitoring cameras which are equipped with intelligent video analytics ability can monitor in different scenes and pre-alarm abnormal behaviors or events. Nevertheless, with the growing number of smart monitoring cameras, the challenges to analytics, storage and retrieval of massive surveillance video data need to be solved in the big data era. This paper proposes an intelligent processing method which makes full use of smart cameras to big surveillance video data. The method consists of three parts: the intelligent pre-alarming for abnormal events, smart storage for surveillance video and rapid retrieval for evidence videos, which aim to improve the utilization efficiency of surveillance video data. Experimental results prove that the proposed approach can reliably pre-alarm abnormal events, efficiently reduce storage space of recorded video and significantly improve the evidence video retrieval rates associated with specific suspects.
2017, 39(5): 1123-1129.
doi: 10.11999/JEIT160710
Abstract:
Concerning the problem that general Fuzzy C-Means (FCM) and its improved algorithm are sensitive to noise in the samples clustering and clustering boundary is not accurate enough, an improved FCM clustering algorithm based on spatial correlation is proposed. Firstly, it can improve the method of clustering center calculation and the function of distance calculation, through analyzing spatial distribution characteristics, interaction and influence value of the samples. Then, it redefines the fuzzy membership matrix through introducing a control parameter during summing membership of the samples with neighborhood information, thus realizing smoothing membership of neighborhood samples. Theoretical analysis and experimental results show that the improved algorithm has a better effect for samples with a lot of noise, and that the regional boundary value can process the image better.
Concerning the problem that general Fuzzy C-Means (FCM) and its improved algorithm are sensitive to noise in the samples clustering and clustering boundary is not accurate enough, an improved FCM clustering algorithm based on spatial correlation is proposed. Firstly, it can improve the method of clustering center calculation and the function of distance calculation, through analyzing spatial distribution characteristics, interaction and influence value of the samples. Then, it redefines the fuzzy membership matrix through introducing a control parameter during summing membership of the samples with neighborhood information, thus realizing smoothing membership of neighborhood samples. Theoretical analysis and experimental results show that the improved algorithm has a better effect for samples with a lot of noise, and that the regional boundary value can process the image better.
2017, 39(5): 1130-1135.
doi: 10.11999/JEIT160779
Abstract:
In order to improve the interpretability and effectiveness of the fuzzy classifier rules, this paper presents a new method to extract the fuzzy rules based on the maximum ball only containing the homogeneous data. At first, every sample constructs a maximum ball in the light of the shortest distance to heterogeneous samples. Then those balls are reduced according to the relation of inclusion and the unique among the samples that the ball encloses. Then the fuzzy rules are constructed with the reserved balls. The parameters learning of the antecedent part of the classifier are based on the minimization of the weight misclassification quadratic error and resolved with the conjugate gradient algorithm. The experiments on 12 benchmark datasets with 10 folds are performed to demonstrate the validity of the classifier.
In order to improve the interpretability and effectiveness of the fuzzy classifier rules, this paper presents a new method to extract the fuzzy rules based on the maximum ball only containing the homogeneous data. At first, every sample constructs a maximum ball in the light of the shortest distance to heterogeneous samples. Then those balls are reduced according to the relation of inclusion and the unique among the samples that the ball encloses. Then the fuzzy rules are constructed with the reserved balls. The parameters learning of the antecedent part of the classifier are based on the minimization of the weight misclassification quadratic error and resolved with the conjugate gradient algorithm. The experiments on 12 benchmark datasets with 10 folds are performed to demonstrate the validity of the classifier.
2017, 39(5): 1136-1141.
doi: 10.11999/JEIT160736
Abstract:
Hybrid Automatic Repeat reQuest (HARQ) scheme with polar codes is suitable for short packets applied to Internet of Things (IoT). Existing HARQ scheme with Chase Combing (HARQ-CC) provides combining gain without coding gain. The HARQ scheme with Incremental Redundancy (HARQ-IR) achieves better performance with significantly high complexity, which is unacceptable for IoT applications. In this paper, an improved HARQ scheme with polar codes is proposed. The proposed coding scheme achieves 0.7 dB gain for code rate R=1/2 and retransmission time T=1 compared with HARQ-CC scheme and the performance of this scheme is approaching the polar codes with rate R=1/4. The encoding and decoding complexity of the proposed scheme is reduced by about 50% compared with the polar codes with rate R=1/4. Simulation results validate the effectiveness of this scheme.
Hybrid Automatic Repeat reQuest (HARQ) scheme with polar codes is suitable for short packets applied to Internet of Things (IoT). Existing HARQ scheme with Chase Combing (HARQ-CC) provides combining gain without coding gain. The HARQ scheme with Incremental Redundancy (HARQ-IR) achieves better performance with significantly high complexity, which is unacceptable for IoT applications. In this paper, an improved HARQ scheme with polar codes is proposed. The proposed coding scheme achieves 0.7 dB gain for code rate R=1/2 and retransmission time T=1 compared with HARQ-CC scheme and the performance of this scheme is approaching the polar codes with rate R=1/4. The encoding and decoding complexity of the proposed scheme is reduced by about 50% compared with the polar codes with rate R=1/4. Simulation results validate the effectiveness of this scheme.
2017, 39(5): 1142-1149.
doi: 10.11999/JEIT160746
Abstract:
The combination of Device-to-Device (D2D) and social networks is one of the hot topics in the current and future communication industry. Cooperative communication is with characteristics of the high data rate and wide coverage range. In order to promote the confidence and the effectiveness between users, for such a cooperative D2D communication network, a comprehensive cooperative D2D relay model is firstly put forward which combines social factors and physical factors. Then, based on the optimization of the outage probability, a relay selection scheme is proposed to reduce the outage probability and improve the system throughput of D2D communication. Furthermore, optimal power allocation of the source and relay equipment is designed. Simulation results show that under the same conditions, the proposed algorithm is superior to other relay selection algorithms with respect to the interruption performance. Moreover, through optimal power allocation, the proposed algorithm can further reduce the outage probability in the D2D cooperative communication system.
The combination of Device-to-Device (D2D) and social networks is one of the hot topics in the current and future communication industry. Cooperative communication is with characteristics of the high data rate and wide coverage range. In order to promote the confidence and the effectiveness between users, for such a cooperative D2D communication network, a comprehensive cooperative D2D relay model is firstly put forward which combines social factors and physical factors. Then, based on the optimization of the outage probability, a relay selection scheme is proposed to reduce the outage probability and improve the system throughput of D2D communication. Furthermore, optimal power allocation of the source and relay equipment is designed. Simulation results show that under the same conditions, the proposed algorithm is superior to other relay selection algorithms with respect to the interruption performance. Moreover, through optimal power allocation, the proposed algorithm can further reduce the outage probability in the D2D cooperative communication system.
2017, 39(5): 1150-1156.
doi: 10.11999/JEIT160590
Abstract:
A novel energy-constrained joint dynamic scheduling and pricing algorithm in wireless cloud computing system is proposed. A Lyapunov function of energy constraints and traffic restrictions is constructed. The long-term profit optimization problem?with multiple?constraints is turned into minimizing the upper bound of Lyapunov offset and weighted penalty function. The algorithm ensures the limited energy requirements of cloud service providers as well as the traffic demands of cloud users, furthermore, it optimizes the long-term profit of cloud service providers.
A novel energy-constrained joint dynamic scheduling and pricing algorithm in wireless cloud computing system is proposed. A Lyapunov function of energy constraints and traffic restrictions is constructed. The long-term profit optimization problem?with multiple?constraints is turned into minimizing the upper bound of Lyapunov offset and weighted penalty function. The algorithm ensures the limited energy requirements of cloud service providers as well as the traffic demands of cloud users, furthermore, it optimizes the long-term profit of cloud service providers.
2017, 39(5): 1157-1163.
doi: 10.11999/JEIT160768
Abstract:
For the sake of reducing the indoor localization errors caused by dynamic signal fading in cellular network, this paper propose a novel Density-Based Spatial Clustering of Applications with Noise (DBSCAN) based subspace matching algorithm for indoor localization, which can improve the localization accuracy by eliminating the location with large errors. Specifically, the signal space is firstly divided into several subspaces, where a position estimation can be obtained respectively using the Weighted K Nearest Neighbors (WKNN) approach. Then, DBSCAN is applied to the position coordinates obtained from each subspace which eliminates the outliers. Finally, the location is estimated based on probability analysis. Experimental results show that the proposed approach can improve the location accuracy by eliminating the location with large errors.
For the sake of reducing the indoor localization errors caused by dynamic signal fading in cellular network, this paper propose a novel Density-Based Spatial Clustering of Applications with Noise (DBSCAN) based subspace matching algorithm for indoor localization, which can improve the localization accuracy by eliminating the location with large errors. Specifically, the signal space is firstly divided into several subspaces, where a position estimation can be obtained respectively using the Weighted K Nearest Neighbors (WKNN) approach. Then, DBSCAN is applied to the position coordinates obtained from each subspace which eliminates the outliers. Finally, the location is estimated based on probability analysis. Experimental results show that the proposed approach can improve the location accuracy by eliminating the location with large errors.
2017, 39(5): 1164-1169.
doi: 10.11999/JEIT161104
Abstract:
In the application of spread spectrum communication with limited wireless resource, Multiple Access Interference (MAI) is the main restraint element of the multiple user service capability and communication performance. Focusing on the MAI problem, lattice reduction theory is firstly applied to the MAI cancellation of spread spectrum communication. A lattice reduction aided multiple user detection method is proposed. With lattice reduction method, the orthogonality of the correlation matrix of multiple signals is improved. As a result, the error bit rate of Multiple User Detection (MUD) method is reduced, and near ML demodulation performance is reached with low complexity. High performance on near-far effect resistance is achieved with the algorithm. Contrary to the performance degradation of traditional MUD method in serious MAI scenario, lattice reduction aided multiple user detection method can maintain near ML performance. Transmission reliability, multiuser service capability and environment suitability of spread spectrum system can be improved remarkably with the algorithm.
In the application of spread spectrum communication with limited wireless resource, Multiple Access Interference (MAI) is the main restraint element of the multiple user service capability and communication performance. Focusing on the MAI problem, lattice reduction theory is firstly applied to the MAI cancellation of spread spectrum communication. A lattice reduction aided multiple user detection method is proposed. With lattice reduction method, the orthogonality of the correlation matrix of multiple signals is improved. As a result, the error bit rate of Multiple User Detection (MUD) method is reduced, and near ML demodulation performance is reached with low complexity. High performance on near-far effect resistance is achieved with the algorithm. Contrary to the performance degradation of traditional MUD method in serious MAI scenario, lattice reduction aided multiple user detection method can maintain near ML performance. Transmission reliability, multiuser service capability and environment suitability of spread spectrum system can be improved remarkably with the algorithm.
2017, 39(5): 1170-1177.
doi: 10.11999/JEIT160642
Abstract:
In 5G and the future mobile communication network, resource management and scheduling are the key issues to achieve efficient service deployment of virtual Evolved Packet Core (vEPC) nerwork. Service deployment in vEPC is based on Service Function Chain (SFC), in which signaling streams and forwarding streams have a big difference. On account of traffic differentiation of mobile network, the proposed model decouples the control layer and transfer layer of SFC. Different layers can make expansion and contraction independently to achieve accurate resources on-demand slice. Utilizing graph similarity theory, a virtual network embedding strategy called VF2-H is put forward in accordance with subgraph isomorphism. Firstly, candidate substrate subnet is preliminary selected on the basis of global resources capacity. Secondly, pruning condition is formulated based on the graph characteristics. Finally, collaborative search strategy is designed according to the characters of vEPC mapping. The simulation results validate the performance of the proposed algorithm in request accepting rate and long-term revenue-to-cost rate.
In 5G and the future mobile communication network, resource management and scheduling are the key issues to achieve efficient service deployment of virtual Evolved Packet Core (vEPC) nerwork. Service deployment in vEPC is based on Service Function Chain (SFC), in which signaling streams and forwarding streams have a big difference. On account of traffic differentiation of mobile network, the proposed model decouples the control layer and transfer layer of SFC. Different layers can make expansion and contraction independently to achieve accurate resources on-demand slice. Utilizing graph similarity theory, a virtual network embedding strategy called VF2-H is put forward in accordance with subgraph isomorphism. Firstly, candidate substrate subnet is preliminary selected on the basis of global resources capacity. Secondly, pruning condition is formulated based on the graph characteristics. Finally, collaborative search strategy is designed according to the characters of vEPC mapping. The simulation results validate the performance of the proposed algorithm in request accepting rate and long-term revenue-to-cost rate.
2017, 39(5): 1178-1184.
doi: 10.11999/JEIT160693
Abstract:
Satisfying non-repeated coverage, connectedness, and energy balance of sink layer are critical problems in multi-layers Wireless Sensor Networks (WSNs). They are overall planed as a Multi-objective Optimization Problem (MOP). For resolving it, the Quantum Wolf Pack Evolutionary Algorithm (QWPEA) is proposed, which actualizes the Candidate Leader Wolf (CLW) selection, sliding mode crossing, quantum rotating gate, and NOR gate mutation are used to obtain the more accurate wolfs location. Simulation results show that QWPEA can minus the number of sink nodes, promote the steadiness, and balance the energy consumption in a huge scale of WSNs effectively. While 1000 sensors are deployed on 800 m800 m with QWPEA, the sink effective coverage ratio is higher than either MOPSO as 29.55% or NSGA-II as 25.93%. And the sink communication energy consumption ratio is higher than the latter two methods as 15.27% and 18.63% separately. Also, the sink occupied ratio is lower than them as 14.01% and 15.46% severally.
Satisfying non-repeated coverage, connectedness, and energy balance of sink layer are critical problems in multi-layers Wireless Sensor Networks (WSNs). They are overall planed as a Multi-objective Optimization Problem (MOP). For resolving it, the Quantum Wolf Pack Evolutionary Algorithm (QWPEA) is proposed, which actualizes the Candidate Leader Wolf (CLW) selection, sliding mode crossing, quantum rotating gate, and NOR gate mutation are used to obtain the more accurate wolfs location. Simulation results show that QWPEA can minus the number of sink nodes, promote the steadiness, and balance the energy consumption in a huge scale of WSNs effectively. While 1000 sensors are deployed on 800 m800 m with QWPEA, the sink effective coverage ratio is higher than either MOPSO as 29.55% or NSGA-II as 25.93%. And the sink communication energy consumption ratio is higher than the latter two methods as 15.27% and 18.63% separately. Also, the sink occupied ratio is lower than them as 14.01% and 15.46% severally.
2017, 39(5): 1185-1192.
doi: 10.11999/JEIT160740
Abstract:
With the emergence of multi-field packet classification such as OpenFlow, the increasing number of match fields, continuous growth in bit-width of entries and ever growing scale of rule set all bring much pressure on the storage space in hardware. To improve the utilization of the existing Ternary Content Addressable Memory (TCAM) resources, a match field reduction scheme Field Trimmer is proposed based on the analysis of rule feature. On the one hand, with the analysis of logical relationships among different match fields, some fields can be merged to reduce the number of match fields. On the other hand, with the analysis of statistical features in a rule set, some of the match fields are picked up to achieve the classification function of the whole set. Experiment result shows that with less algorithm complexity, the proposed scheme can save around 50% storage space in the rule set of OpenFlow compared to the best prior art, and about 40% storage space in the popular 5-tuple packet classification rule set.
With the emergence of multi-field packet classification such as OpenFlow, the increasing number of match fields, continuous growth in bit-width of entries and ever growing scale of rule set all bring much pressure on the storage space in hardware. To improve the utilization of the existing Ternary Content Addressable Memory (TCAM) resources, a match field reduction scheme Field Trimmer is proposed based on the analysis of rule feature. On the one hand, with the analysis of logical relationships among different match fields, some fields can be merged to reduce the number of match fields. On the other hand, with the analysis of statistical features in a rule set, some of the match fields are picked up to achieve the classification function of the whole set. Experiment result shows that with less algorithm complexity, the proposed scheme can save around 50% storage space in the rule set of OpenFlow compared to the best prior art, and about 40% storage space in the popular 5-tuple packet classification rule set.
2017, 39(5): 1193-1199.
doi: 10.11999/JEIT160792
Abstract:
Virtual machine migration is one of the important features of the data center, which can effectively balance the workload of each infrastructure. In order to reduce the total time of virtual machine migration and impact on service performance, a Heuristic Algorithm based on Cost Evaluation (HACE) is proposed in this paper. The proposed algorithm considers both the residual bandwidth of the network and migration time in every step of the virtual machine migration. And through organic combination of parallel algorithm and heuristic algorithm, it solves migration sequence problem of numerous virtual machines in Software Defined Network (SDN). The algorithm reduces the total migration time of the virtual machine while ensuring the security, dependence and performance requirements. Comparing with the greedy algorithm, experiments show that the algorithm can reduce the total migration time of the virtual machine by up to 52.1%, improve the migration performance and ensure the quality of service.
Virtual machine migration is one of the important features of the data center, which can effectively balance the workload of each infrastructure. In order to reduce the total time of virtual machine migration and impact on service performance, a Heuristic Algorithm based on Cost Evaluation (HACE) is proposed in this paper. The proposed algorithm considers both the residual bandwidth of the network and migration time in every step of the virtual machine migration. And through organic combination of parallel algorithm and heuristic algorithm, it solves migration sequence problem of numerous virtual machines in Software Defined Network (SDN). The algorithm reduces the total migration time of the virtual machine while ensuring the security, dependence and performance requirements. Comparing with the greedy algorithm, experiments show that the algorithm can reduce the total migration time of the virtual machine by up to 52.1%, improve the migration performance and ensure the quality of service.
A Novel Adaptive Cross-layer Broadcasting Protocol NABP for Three-dimensional Flying Ad Hoc Networks
2017, 39(5): 1200-1205.
doi: 10.11999/JEIT160687
Abstract:
To alleviate the broadcast storm problem caused by blind flooding, a Novel Adaptive Broadcasting Protocol (NABP) for three-dimensional Flying Ad hoc NETworks (FANETs) is proposed. NABP adopts the cross-layer design, which lets routing layer share the received signal power information at MAC layer while still maintaining separation between the two layers. The additional transmission range that can benefit from rebroadcast is calculated according to the received signal power, which is applied to dynamically adjust the rebroadcast probability. NABP reduces the redundant retransmission and the chance of the contention and collision among neighboring nodes in the networks. The simulation results demonstrate preliminarily that NABP improves the saved rebroadcast and reduces the average end-to-end delay and the average number of packet loss per node at the expense of a little throughput, which all compare NABP with flooding+802.11 and fp-flooding+802.11.
To alleviate the broadcast storm problem caused by blind flooding, a Novel Adaptive Broadcasting Protocol (NABP) for three-dimensional Flying Ad hoc NETworks (FANETs) is proposed. NABP adopts the cross-layer design, which lets routing layer share the received signal power information at MAC layer while still maintaining separation between the two layers. The additional transmission range that can benefit from rebroadcast is calculated according to the received signal power, which is applied to dynamically adjust the rebroadcast probability. NABP reduces the redundant retransmission and the chance of the contention and collision among neighboring nodes in the networks. The simulation results demonstrate preliminarily that NABP improves the saved rebroadcast and reduces the average end-to-end delay and the average number of packet loss per node at the expense of a little throughput, which all compare NABP with flooding+802.11 and fp-flooding+802.11.
2017, 39(5): 1206-1212.
doi: 10.11999/JEIT160621
Abstract:
With the development of cloud computing, more and more users employ cloud-based Personal Health Record (PHR) systems. The PHR is correlated with patient privacy, thus existing research suggests to encrypt PHRs before outsourcing. Comparison-Based Encryption (CBE) realizes time comparison in attribute-based access policy, however, the time for encryption is linearly with the number of attributes in the access policy. Therefore, the cost of the scheme is extensive; besides, the scheme is difficult to revoke the user's access privileges in real time. To realize efficiently a fine-grained access control and user revocation for PHRs in clouds, a Fine-Grained access control with User Revocation (FGUR) scheme is proposed by incorporating Broadcast Ciphertext-Policy Attribute-Based Encryption (BCP-ABE) and an attribute hierarchy into CBE. The experiment results show that the FGUR scheme has better performance in terms of the encryption cost and dynamic access privilege, compared with CBE.
With the development of cloud computing, more and more users employ cloud-based Personal Health Record (PHR) systems. The PHR is correlated with patient privacy, thus existing research suggests to encrypt PHRs before outsourcing. Comparison-Based Encryption (CBE) realizes time comparison in attribute-based access policy, however, the time for encryption is linearly with the number of attributes in the access policy. Therefore, the cost of the scheme is extensive; besides, the scheme is difficult to revoke the user's access privileges in real time. To realize efficiently a fine-grained access control and user revocation for PHRs in clouds, a Fine-Grained access control with User Revocation (FGUR) scheme is proposed by incorporating Broadcast Ciphertext-Policy Attribute-Based Encryption (BCP-ABE) and an attribute hierarchy into CBE. The experiment results show that the FGUR scheme has better performance in terms of the encryption cost and dynamic access privilege, compared with CBE.
2017, 39(5): 1213-1218.
doi: 10.11999/JEIT160829
Abstract:
Heterogeneous signcryption can ensure the confidentiality, authentication and unforgeability of information transmission of cross cryptograph environment. Through analyzing some existing heterogeneous signcryption schemes, it is found that they can only be applicable to single message of signcryption. In order to improve the efficiency of computation and transmission in heterogeneous systems, a provable multi-message aggregate signcryption is proposed. In the new scheme, the pairing numbers are constant in verification phase, it not depends on the number of signcryption message. Moreover, based on the assumption of q-bilinear Diffie- Hellman inversion issue and Discrete logarithm, in the random oracle model, it is proved that the new scheme satisfies the properties of confidentiality and unforgeability. Furthermore, theoretical analysis and experimental results demonstrate that the computation overhead efficiency of the proposed scheme is better than the existing one.
Heterogeneous signcryption can ensure the confidentiality, authentication and unforgeability of information transmission of cross cryptograph environment. Through analyzing some existing heterogeneous signcryption schemes, it is found that they can only be applicable to single message of signcryption. In order to improve the efficiency of computation and transmission in heterogeneous systems, a provable multi-message aggregate signcryption is proposed. In the new scheme, the pairing numbers are constant in verification phase, it not depends on the number of signcryption message. Moreover, based on the assumption of q-bilinear Diffie- Hellman inversion issue and Discrete logarithm, in the random oracle model, it is proved that the new scheme satisfies the properties of confidentiality and unforgeability. Furthermore, theoretical analysis and experimental results demonstrate that the computation overhead efficiency of the proposed scheme is better than the existing one.
2017, 39(5): 1219-1225.
doi: 10.11999/JEIT160795
Abstract:
In order to meet the demand of modern communication, multiuser access technology is an important development trend of current chaotic communication. To improve the Bit Error Rate (BER) performance of the existing multiuser chaotic communication schemes, a MultiUser communication scheme based on Segment Shift Differential Chaos Shift Keying (MU-SSDCSK) is proposed. According to the users number in transmission, the reference signal of MU-SSDCSK is divided intom segments, which are then shifted and matched with different Walsh codes that therefore can make the information-bearing signals orthogonal to each other. The theoretical BER formula of this new scheme is derived in Additive White Gaussian Noise (AWGN) channel. The simulation results show that the proposed scheme can effectively improve BER performance, and has certain application prospect in the chaotic communication field.
In order to meet the demand of modern communication, multiuser access technology is an important development trend of current chaotic communication. To improve the Bit Error Rate (BER) performance of the existing multiuser chaotic communication schemes, a MultiUser communication scheme based on Segment Shift Differential Chaos Shift Keying (MU-SSDCSK) is proposed. According to the users number in transmission, the reference signal of MU-SSDCSK is divided intom segments, which are then shifted and matched with different Walsh codes that therefore can make the information-bearing signals orthogonal to each other. The theoretical BER formula of this new scheme is derived in Additive White Gaussian Noise (AWGN) channel. The simulation results show that the proposed scheme can effectively improve BER performance, and has certain application prospect in the chaotic communication field.
2017, 39(5): 1226-1232.
doi: 10.11999/JEIT160733
Abstract:
In order to solve the problem that the Non-Linear Boolean Function (NLBF) unit in sequence cryptogram possesses poor hardware resource utilization, the utilization model of basic component composed by Look-Up Table (LUT) is studied and three essential parameters (LUT size, cluster scale and the number of input ports) which impact hardware utilization are decided combined with the early processing results of adaption algorithm. On the basis, the mapping of NLBF limited to variable frequency is realized and the design of nonlinear computing unit is implemented, which can support multi-way parallel processing. The circuit is developed and synthesized in SMIC 180 nm. Its working frequency realizes 241 MHz and it achieves the maximum throughput of 7.71 Gb/s in parallelism of 32. The results after evaluating the utilization of various NLBFs show that all utilization can reach over 91.14% and the utilization increases continually as the parallelism increases.
In order to solve the problem that the Non-Linear Boolean Function (NLBF) unit in sequence cryptogram possesses poor hardware resource utilization, the utilization model of basic component composed by Look-Up Table (LUT) is studied and three essential parameters (LUT size, cluster scale and the number of input ports) which impact hardware utilization are decided combined with the early processing results of adaption algorithm. On the basis, the mapping of NLBF limited to variable frequency is realized and the design of nonlinear computing unit is implemented, which can support multi-way parallel processing. The circuit is developed and synthesized in SMIC 180 nm. Its working frequency realizes 241 MHz and it achieves the maximum throughput of 7.71 Gb/s in parallelism of 32. The results after evaluating the utilization of various NLBFs show that all utilization can reach over 91.14% and the utilization increases continually as the parallelism increases.
2017, 39(5): 1233-1244.
doi: 10.11999/JEIT160716
Abstract:
Given a graphG and a proper vertex coloring ofG, a 2-coloring induced subgraph ofG is a subgraph induced by all the vertices with one of two colors, a component of a 2-coloring induced subgraph is called a 2-coloring component. To make a Kempe change is to obtain one coloring from another by exchanging the colors of vertices in a 2-coloring component. Two colorings are Kempe equivalent if each one can be obtained from the other by a series of Kempe changes. Mohar conjectured that, for k3, all k-colorings of connected k-regular graphs that are not complete are Kempe equivalent. Feghali et al. addressed the case k=3, and it is still an unsolved conjecture for k4. This paper considers the casek=4 by showing that: (1) ifG is a connected 4-regular graph that is not 3-connected, then all 4-colorings ofG are Kempe equivalent; (2) ifG is a connected 4-regular graph that contains an induced subgraph isomorphic to a 4-wheel or a nearly complete graph of order 5, then all 4-colorings ofG are Kempe equivalent; (3) ifG is a 3-connceted 4-regular graph with a 4-coloringf and a vertexx such that there are three or four neighbors ofx colored with the same color under f, then all 4-colorings ofG are Kempe equivalent.
Given a graphG and a proper vertex coloring ofG, a 2-coloring induced subgraph ofG is a subgraph induced by all the vertices with one of two colors, a component of a 2-coloring induced subgraph is called a 2-coloring component. To make a Kempe change is to obtain one coloring from another by exchanging the colors of vertices in a 2-coloring component. Two colorings are Kempe equivalent if each one can be obtained from the other by a series of Kempe changes. Mohar conjectured that, for k3, all k-colorings of connected k-regular graphs that are not complete are Kempe equivalent. Feghali et al. addressed the case k=3, and it is still an unsolved conjecture for k4. This paper considers the casek=4 by showing that: (1) ifG is a connected 4-regular graph that is not 3-connected, then all 4-colorings ofG are Kempe equivalent; (2) ifG is a connected 4-regular graph that contains an induced subgraph isomorphic to a 4-wheel or a nearly complete graph of order 5, then all 4-colorings ofG are Kempe equivalent; (3) ifG is a 3-connceted 4-regular graph with a 4-coloringf and a vertexx such that there are three or four neighbors ofx colored with the same color under f, then all 4-colorings ofG are Kempe equivalent.
2017, 39(5): 1245-1249.
doi: 10.11999/JEIT160647
Abstract:
In view of the difficulty of implementing the narrow band and integration simultaneously for the traditional Ka-band filter, a Ka-band filter with narrow pass band is designed based on Substrate Integrated Waveguide (SIW). The filter adopts the structure with dual-mode circle cavity and ellipse cavity cascaded, which achieves the advantages of high frequency selectivity due to the transmission zeros both in upper and lower sideband. The measured results show that the filter has a relative bandwidth of 2.85%, insertion loss of 3.4 dB, and return loss is more than 15 dB at a center frequency 35 GHz, and the results are in good agreement with the simulation results. The measured results verify that the filter has great application value in millimeter system.
In view of the difficulty of implementing the narrow band and integration simultaneously for the traditional Ka-band filter, a Ka-band filter with narrow pass band is designed based on Substrate Integrated Waveguide (SIW). The filter adopts the structure with dual-mode circle cavity and ellipse cavity cascaded, which achieves the advantages of high frequency selectivity due to the transmission zeros both in upper and lower sideband. The measured results show that the filter has a relative bandwidth of 2.85%, insertion loss of 3.4 dB, and return loss is more than 15 dB at a center frequency 35 GHz, and the results are in good agreement with the simulation results. The measured results verify that the filter has great application value in millimeter system.
Induced Fields Produced on Iron Rotation Long Ellipsoid Cavity under Uniform Constant Magnetic Field
2017, 39(5): 1250-1255.
doi: 10.11999/JEIT160683
Abstract:
The shape of the submarine is idealized as a rotation symmetrical long ellipsoid cavity in order to study the induced fields around the submarine. The expressions of the induced magnetic fields in inside and outside cavity are derived. The contour distributions of the total induced magnetic field and each component on the cavity along different latitudes, different location directions and different detection heights are analyzed and discussed by the analytical method under the uniform constant magnetic field. The calculation results indicate that the induced magnetic fields will gradually die down along with the increase of the propagation distance. The induced magnetic field is prominent along the cavity longitudinal direction (z component), while it is minimum along the cavity vertical direction (x component). The total induced magnetic field and each component detected by the magnetometer at middle latitude can be more easily detected than those at high latitude. While their detection ranges change very little along with the increase of the height. It can be more easily detected when the cavity is placed along the south and north direction.
The shape of the submarine is idealized as a rotation symmetrical long ellipsoid cavity in order to study the induced fields around the submarine. The expressions of the induced magnetic fields in inside and outside cavity are derived. The contour distributions of the total induced magnetic field and each component on the cavity along different latitudes, different location directions and different detection heights are analyzed and discussed by the analytical method under the uniform constant magnetic field. The calculation results indicate that the induced magnetic fields will gradually die down along with the increase of the propagation distance. The induced magnetic field is prominent along the cavity longitudinal direction (z component), while it is minimum along the cavity vertical direction (x component). The total induced magnetic field and each component detected by the magnetometer at middle latitude can be more easily detected than those at high latitude. While their detection ranges change very little along with the increase of the height. It can be more easily detected when the cavity is placed along the south and north direction.
2017, 39(5): 1256-1260.
doi: 10.11999/JEIT160637
Abstract:
In order to improve the efficiency of attack and reduce the influence of noise on power analysis, a growing number of preprocessing methods are discussed and numerous remarkable results are reported. The AES-128 algorithm running on the ATmega16 is taken as the target in this paper. The original energy curves are moved average and the optimal parameter of moving average filter is determined by Correlation Power Analysis (CPA) subsequently. The experimental results demonstrate that compared with the original data and the data after Hanning window low-pass filter, the correlation coefficient obtained by the correct key with the using of moving average filter is evidently promoted, while the correlation coefficient obtained by the incorrect key is decreased. With the moving average approaching, the process of the ten encryption of AES-128 can be discovered obviously. The peak of Differential Power Analysis (DPA)obtained by the data using moving average is more obvious than that obtained by the original data. Numerical results show that the moving average approaching can improve the efficiency of power analysis evidently.
In order to improve the efficiency of attack and reduce the influence of noise on power analysis, a growing number of preprocessing methods are discussed and numerous remarkable results are reported. The AES-128 algorithm running on the ATmega16 is taken as the target in this paper. The original energy curves are moved average and the optimal parameter of moving average filter is determined by Correlation Power Analysis (CPA) subsequently. The experimental results demonstrate that compared with the original data and the data after Hanning window low-pass filter, the correlation coefficient obtained by the correct key with the using of moving average filter is evidently promoted, while the correlation coefficient obtained by the incorrect key is decreased. With the moving average approaching, the process of the ten encryption of AES-128 can be discovered obviously. The peak of Differential Power Analysis (DPA)obtained by the data using moving average is more obvious than that obtained by the original data. Numerical results show that the moving average approaching can improve the efficiency of power analysis evidently.
2017, 39(5): 1261-1265.
doi: 10.11999/JEIT160651
Abstract:
Base on Lagrange multiplier method, an iterative algorithm is proposed to design the two-dimensional modified Discrete Fourier Transform (DFT) modulated filter bank. In each iteration, the design problem is described as a Quadratically Constrained Quadratic Program (QCQP). The Lagrange multiplier method is then employed to transform the constrained problem into an unconstrained one, the solution of which is obtained by solving a set of linear equations. By analyzing the coefficient matrix, block LU factorization is applied to considerably reduce the computational complexity. Numerical results and comparison with the existing methods demonstrate the improved performance of the proposed scheme, including the reconstruction error and stopband attenuation.
Base on Lagrange multiplier method, an iterative algorithm is proposed to design the two-dimensional modified Discrete Fourier Transform (DFT) modulated filter bank. In each iteration, the design problem is described as a Quadratically Constrained Quadratic Program (QCQP). The Lagrange multiplier method is then employed to transform the constrained problem into an unconstrained one, the solution of which is obtained by solving a set of linear equations. By analyzing the coefficient matrix, block LU factorization is applied to considerably reduce the computational complexity. Numerical results and comparison with the existing methods demonstrate the improved performance of the proposed scheme, including the reconstruction error and stopband attenuation.
2017, 39(5): 1266-1270.
doi: 10.11999/JEIT160548
Abstract:
A detailed analysis of the fault features for the block cipher is performed, and an analysis framework for propagation of faults is proposed. Furthermore, a security evaluation methodology with single fault injection or multi fault injection is presented. The experiment results show that the change of the key space for the block cipher, using different fault attacks, can be charactered effectively and the ability of the fault-resistant can be presented well.
A detailed analysis of the fault features for the block cipher is performed, and an analysis framework for propagation of faults is proposed. Furthermore, a security evaluation methodology with single fault injection or multi fault injection is presented. The experiment results show that the change of the key space for the block cipher, using different fault attacks, can be charactered effectively and the ability of the fault-resistant can be presented well.
