一种引入自适应动量项的变步长混沌信号盲分离算法

张天骐; 马宝泽; 强幸子; 全盛荣

doi:10.11999/JEIT160578

一种引入自适应动量项的变步长混沌信号盲分离算法

doi: 10.11999/JEIT160578

基金项目:

国家自然科学基金(61671095, 61371164, 61275099)，信号与信息处理重庆市市级重点实验室建设项目(CSTC2009CA2003)，重庆市教育委员会科研项目(KJ130524, KJ1600427, KJ1600429)

计量
- 文章访问数: 1276
- HTML全文浏览量: 154
- PDF下载量: 462
- 被引次数: 0
出版历程
- 收稿日期: 2016-06-03
- 修回日期: 2016-11-28
- 刊出日期: 2017-04-19

Variable-step Blind Source Separation Algorithm with Adaptive Momentum Item for Chaotic Signals

Funds:

The National Natural Science Foundation of China (61671095, 61371164, 61275099), The Project of Key Laboratory of Signal and Information Processing of Chongqing (CSTC2009CA2003), The Research Project of Chongqing Educational Commission (KJ130524, KJ1600427, KJ1600429)

摘要

摘要: 该文针对混沌信号盲分离问题，提出一种改进盲分离算法。该算法利用信号分离评价指标来构造函数实现步长和动量因子的自适应调整，然后将构造函数代入盲分离算法中并引入自适应动量项。区别于大多数算法不对混合矩阵进行估计的问题，该算法用变步长函数迭代估计出混合矩阵，从而得到全局矩阵和估计评价指标，以此迭代更新步长和动量因子，最终得出分离矩阵。仿真表明，该算法依据估计评价指标构造函数调整步长和动量因子方法是有效的，在平稳和非平稳环境下对混合混沌信号分离时都能达到收敛速度快且稳态误差小的效果；在混入色噪声时，比传统算法抗噪性能好，表明该文算法在混沌信号盲分离处理中有一定应用价值。
- 盲源分离 /
- EASI算法 /
- 混沌信号 /
- 动量因子 /
- 变步长
Abstract: To solve the problem of blind source separation for chaotic signals, an improved blind separation algorithm is proposed. A function is constructed by signal separation evaluation index, which adaptively updates the step size and momentum factor, then substitutes the obtained variable step-size function into blind source separation algorithm and introduces the adaptive momentum item. Different from most algorithms which can not estimate the mixing matrix, the proposed algorithm estimates iteratively the mixing matrix by the variable step function, then the global matrix and the estimated evaluation can be obtained on which step and momentum factor are iteratively updated. Finally, the separation matrix is obtained. Simulations show that the algorithm is effective to adjust the step and momentum factor based on the estimated evaluation index constructor. In stationary and non-stationary environments, the algorithm has faster convergence speed and lower steady error for separating the mixed chaotic signals. When mixing color noise, the proposed algorithm is better than that of the traditional algorithm, which shows that the proposed algorithm has certain application value to the chaotic signal blind source separation processing.
- Blind source separation /
- EASI algorithm /
- Chaotic signals /
- Momentum factor /
- Variable-step

HTML全文

参考文献(29)

禹思敏, 吕金虎, 李澄清. 混沌密码及其在多媒体保密通信中应用的进展[J]. 电子与信息学报, 2016, 38(3): 735-752. doi: 10.11999/JEIT151356.

YU Simin, L Jinhu, and LI Chengqing. Some progresses of chaotic cipher and its applications in multimedia secure communications[J]. Journal of Electronics Information Technology, 2016, 38(3): 735-752. doi: 10.11999/JEIT151356.

黄宇, 刘玉峰, 彭志敏, 等. 基于量子并行粒子群优化算法的分数阶混沌系统参数估计[J]. 物理学报, 2015, 64(3): 228-235. doi: 10.7498/aps.64.030505.

HUANG Yu, LIU Yufeng, PENG Zhimin, et al. Research on particle swarm optimization algorithm with characteristic of quantum parallel and its application in parameter estimation for fractional-order chaotic systems[J]. Acta Physica Sinica, 2015, 64(3): 228-235. doi: 10.7498/aps.64.030505.

黄锦旺, 冯久超, 吕善翔. 混沌信号在无线传感器网络中的盲分离[J]. 物理学报, 2014, 63(5): 50502. doi: 10.7498/aps.63. 050502.

HUANG Jinwang, FENG Jiuchao, and L Shanxiang. Blind source separation of chaotic signals in wireless sensor networks[J]. Acta Physica Sinica, 2014, 63(5): 50502. doi: 10.7498/aps.63.050502.

王世元, 冯久超. 一种新的参数估计方法及其在混沌信号盲分离中的应用[J]. 物理学报, 2012, 61(17): 170508. doi: 05.45.-a,05.45.Vx,84.40.Ua.

WANG Shiyuan and FENG Jiuchao. A novel method of estimating parameter and its application to blind separation of chaotic signals[J]. Acta Physica Sinica, 2012, 61(17): 170508. doi: 05.45.-a,05.45.Vx,84.40.Ua.

陈越, 吕善翔, 王梦蛟, 等. 一种基于人工蜂群算法的混沌信号盲分离方法[J]. 物理学报, 2015, 64(9): 090501. doi: 10.7498 /aps.64.090501.

CHEN Yue, L Shanxiang, WANG Mengjiao, et al. A blind source separation method for chaotic signals based on artificial bee colony algorithm[J]. Acta Physica Sinica, 2015, 64(9): 090501. doi: 10.7498/aps.64.090501.

OU Shifeng, WANG Xianyun, and GAO Ying. Adaptive improved RLS algorithm for blind source separation[J]. Wydawnictwo SIGMA-NOT, 2013, 89(3b): 81-83.

欧世峰, 高颖, 赵晓晖. 自适应组合型盲源分离算法及其优化方案[J]. 电子与信息学报, 2011, 33(5): 1243-1247. doi: 10.3724/SP.J.1146.2010.00871.

OU Shifeng, GAO Ying, and ZHAO Xiaohui. Adaptive combination algorithm and its modified scheme for blind source separation [J]. Journal of Electronics Information Technology, 2011, 33(5): 1243-1247. doi: 10.3724/SP.J.1146. 2010.00871.

欧世峰, 高颖, 赵晓晖. 基于随机梯度的变动量因子自适应白化算法[J]. 自动化学报, 2012, 38(8): 1370-1374. doi: 10.3724/ SP.J.1004.2012.01370.

OU Shifeng, GAO Ying, and ZHAO Xiaohui. Stochastic gradient based variable momentum factor algorithm for adaptive whitening[J]. Acta Automatica Sinica, 2012, 38(8): 1370-1374. doi: 10.3724/SP.J.1004.2012.01370.

欧世峰, 耿超, 高颖. 动量项盲源分离算法及其性能优化策略[J]. 电子学报, 2014, 42(1): 42-48. doi: 10. 3969/j.issn.0372- 2112.2014.01.007.

OU Shifeng, GENG Chao, and GAO Ying. Momentum term based blind source separation algorithm and its performance modified strategies[J]. Acta Electronica Sinica, 2014, 42(1): 42-48. doi: 10.3969/j.issn.0372-2112.2014.01.007.

PAL M, ROY R, BASU J, et al. Blind source separation: A review and analysis[C]. Oriental Cocosda Held Jointly with 2013 Conference on Asian Spoken Language Research and Evaluation. Gurgaon, India, 2013: 1-5.

季策, 杨坤, 陶奕名, 等. 一种非平稳环境下的自适应变步长盲源分离算法[J]. 控制与决策, 2016, 31(4): 735-739. doi: 10.13195/j.kzyjc.2015.0170.

JI Ce, YANG Kun,TAO Yiming, et al. An adaptive variable step-size blind source separation algorithm in nonstationary environment[J]. Control and Decision, 2016, 31(4): 735-739. doi: 10.13195/j.kzyjc.2015.0170.

CARDOSO J F and LAHELD B H. Equivariant adaptive source separation[J]. IEEE Transactions on Signal Processing, 1997, 44(12): 3017-3030.

MKADEM F and BOUMAIZA S. Physically inspired neural network model for RF power amplifier behavioral modeling and digital predistortion[J]. IEEE Transactions on Microwave Theory Techniques, 2011, 59(4): 913-923.

张贤达. 矩阵分析与应用[M]. 北京: 清华大学出版社, 2004: 310-314.

ZHANG Xianda. Matrix Analysis and Applications[M]. Beijing: Tsinghua University Press, 2004: 310-314.

XU P, SHEN Y, and SU Q. Blind source separation with variable step-size method based on a reference separation system[C]. IEEE International Conference on Signal Processing, Communications and Computing. Guilin, 2014: 110-114.

季策, 杨坤, 王艳茹, 等. 基于符号算子的变步长不完整自然梯度算法[J]. 模式识别与人工智能, 2014, 27(11): 1026-1031. doi: 10.16451/j.cnki.issn1003-6059.2014.11.002.

JI Ce, YANG Kun, WANG Yanru, et al. Variable step-size nonholonomic natural gradient algorithm based on sign operator[J]. Pattern Recogniton and Artificial Intelligence, 2014, 27(11): 1026-1031. doi: 10.16451/j.cnki.issn1003-6059. 2014.11.002.

徐成发, 郝宇星, 陆潞, 等. 基于互相关的快速角度估计算法[J].电子与信息学报, 2016, 38(6): 1446-1451. doi: 10.11999/ JEIT151021.

XU Chengfa, HAO Yuxing, LU Lu, et al. Fast angle estimation algorithm based on cross-correlation[J]. Journal of Electronics Information Technology, 2016, 38(6): 1446-1451. doi: 10.11999/JEIT151021.

施引文献

资源附件(0)

访问统计