中国物理B(英文版)2024,Vol.33Issue(1) :290-300.DOI:10.1088/1674-1056/ad01a8

Research and application of composite stochastic resonance in enhancement detection

高蕊 焦尚彬 薛琼婕
中国物理B(英文版)2024,Vol.33Issue(1) :290-300.DOI:10.1088/1674-1056/ad01a8

Research and application of composite stochastic resonance in enhancement detection

高蕊 1焦尚彬 2薛琼婕2
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作者信息

  • 1. School of Automation and Information Engineering,Xi'an University of Technology,Xi'an 710048,China;School of Electronic and Electrical Engineering,Baoji University of Arts and Sciences,Baoji 721016,China
  • 2. School of Automation and Information Engineering,Xi'an University of Technology,Xi'an 710048,China;Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing,Xi'an University of Technology,Xi'an 710048,China
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Abstract

Aiming at the problem that the intermediate potential part of the traditional bistable stochastic resonance model cannot be adjusted independently,a new composite stochastic resonance(NCSR)model is proposed by combining the Woods-Saxon(WS)model and the improved piecewise bistable model.The model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation,all the parameters in the new model have no coupling characteristics.Under α stable noise environment,the new model is used to detect periodic signal and aperiodic signal,the detection results indicate that the new model has higher noise utilization and better detection effect.Finally,the new model is applied to image denoising,the results showed that under the same conditions,the output peak signal-to-noise ratio(PSNR)and the correlation number of NCSR method is higher than that of other commonly used linear denoising methods and improved piecewise SR methods,the effectiveness of the new model is verified.

Key words

Woods-Saxon/improved piecewise model/composite stochastic resonance(SR)/image denoising

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基金项目

National Natural Science Foundation of China(62371388)

Key Research and Development Projects in Shaanxi Province,China(2023-YBGY-044)

出版年

2024
中国物理B(英文版)
中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI
影响因子:0.995
ISSN:1674-1056
参考文献量36
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