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Multi-Stable Stochastic Resonance Model Based on High-Order Time-Delay Feedback Control and Its Application in Weak Signal Detection

EasyChair Preprint 10980

11 pagesDate: September 28, 2023

Abstract

The noise transfer capability of stochastic resonance makes it excellent in the field of weak signal detection. The classic bistable potential well has a simple structure, few parameters and is easy to observe in the physical system, so that a lot of research is carried out based on the bistable stochastic resonance. However, multi-stable potential wells can induce multiple stable responses in nonlinear systems, thereby improving the signal-to-noise ratio(SNR) of the system output signal. In order to break the short-memory effect of the classical stochastic resonance system, a multi-stable stochastic resonance model based on high-order time-delay feedback control(HTFMSR) is proposed in this paper, and it is used for weak signal detection. First, the stochastic resonance effect of the HTFNSR system is demonstrated by deriving the theoretical output SNR. Subsequently, the influence of delay parameters on the system output is studied through the generalized potential function of the system, the steady-state probability density function and the average first transit time. Finally, the weak signal detection ability of the proposed method is verified by two different examples. The experimental results show that the high-order delay feedback item can improve the memory characteristics of the system and improve the signal-to-noise ratio of the output signal of the system.

Keyphrases: Time-delay Feedback, stochastic resonance, weak signal detection

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:10980,
  author    = {Wenyue Zhang and Bin Zhang and Yongfei Guo},
  title     = {Multi-Stable Stochastic Resonance Model Based on High-Order Time-Delay Feedback Control and Its Application in Weak Signal Detection},
  howpublished = {EasyChair Preprint 10980},
  year      = {EasyChair, 2023}}
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