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The Application of Stochastic Resonance for Weak signal Extraction from Strong Noise

Xianglong Yang

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Abstract

In order to detect weak signals overwhelmed in noise, the method of signal detection is investigated using the principle of stochastic resonance. In this paper, relationship between the structure parameters of the nonlinear system, signal and noise is extensively studied. Comparison between the signals before and after passing through the stochastic resonator is given. It is proved that stochastic resonance is a very useful tool for weak signal extraction from strong noise.

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What this paper is about

In order to detect weak signals overwhelmed in noise, the method of signal detection is investigated using the principle of stochastic resonance. In this paper, relationship between the structure parameters of the nonlinear system, signal and noise is extensively studied. Comparison between the signals before and after passing through the stochastic resonator is given. It is proved that stochastic resonance is a very useful tool for weak signal extraction from strong noise.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In order to detect weak signals overwhelmed in noise, the method of signal detection is investigated using the principle of stochastic resonance. In this paper, relationship between the structure parameters of the nonlinear system, signal and noise is extensively studied. Comparison between the signals before and after passing through the stochastic resonator is given. It is proved that stochastic resonance is a very useful tool for weak signal extraction from strong noise.

Key concepts: Stochastic resonance, Noise (video), SIGNAL (programming language), Resonator, Nonlinear system, Acoustics, Resonance (particle physics), Signal transfer function

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