Time-varying Signal Detection and Recovery Method Based on Varying Parameter Stochastic Resonance and Normalization Transformation

Zhang Hai-bin; He Qing-bo; Kong Fan-rang

doi:10.11999/JEIT141618

Volume 37 Issue 9

Sep. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(9): 2124-2131

Zhang Hai-bin, He Qing-bo, Kong Fan-rang. Time-varying Signal Detection and Recovery Method Based on Varying Parameter Stochastic Resonance and Normalization Transformation[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2124-2131. doi: 10.11999/JEIT141618

Citation:

Zhang Hai-bin, He Qing-bo, Kong Fan-rang. Time-varying Signal Detection and Recovery Method Based on Varying Parameter Stochastic Resonance and Normalization Transformation[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2124-2131. doi: 10.11999/JEIT141618

Citation:

Zhang Hai-bin, He Qing-bo, Kong Fan-rang. Time-varying Signal Detection and Recovery Method Based on Varying Parameter Stochastic Resonance and Normalization Transformation[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2124-2131. doi: 10.11999/JEIT141618

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Time-varying Signal Detection and Recovery Method Based on Varying Parameter Stochastic Resonance and Normalization Transformation

doi: 10.11999/JEIT141618

Received Date: 2014-12-18
Rev Recd Date: 2015-02-15
Publish Date: 2015-09-19

Abstract

Abstract

The nonlinear stochastic resonance system has the ability to take advantage of background noise to enhance the weak signal among it. It provides the new approach to detect the weak signal embedded with heavy noise. This study proposes a new Varying Parameter Stochastic Resonance (VPSR) model. The model performs well in the detection of a time-varying signal with noise as well as the denoising and signal recovery. This study takes the determination coefficient and cross correlation coefficient as the criteria and analyzes the influence of different parameters variation on the system output. The simulation results indicate the model performs better in the time-varying signal recovery than the traditional one. The proposed method develops the area of time-varying signal detection with stochastic resonance which can be hoped to be widely used in the aperiodic signal processing, radar communication, etc. due to its superiority.
- Signal processing,
- Varying Parameter Stochastic Resonance (VPSR),
- Time-varying signal,
- Weak signal detection,
- Signal recovery

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References(27)

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