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Theory and method for weak signal detection in engineering practice based on stochastic resonance

机译:基于随机共振的工程实践中弱信号检测理论与方法

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摘要

In this paper, the Kramers rate was derived using the Fokker Planck (FP) equation with the condition of adiabatic approximation (the amplitude and frequency of signal detected are small 1) and the signal-to-noise ratio (SNR) was proved by means of Fourier transform and the power spectrum in bistable system. This is a concise and superior method to demonstrate the Kramers rate and SNR compared to the past methods. It is convenient for readers to understand. The SNR of the bistable system obtained shows that stochastic resonance (SR) can be used to realize energy transition from noise to a periodic signal under the adiabatic approximation condition. Therefore, SR could enhance the SNR of the output signal. The signal modulation technique was employed to transform the large frequency components into a small parameter signal to meet the adiabatic approximation requirement. Furthermore, we have designed the model of modulator. The simulation results show that the modulation method can generate SR in a bistable system and detect weak signals with large parameters from strong noise background.
机译:在本文中,使用Fokker Planck(FP)方程来导出kramers速率,其具有绝热近似的条件(检测到的信号的幅度和频率是小 1),并且证明了信噪比(SNR)通过傅立叶变换和双稳态系统中的功率谱。这是一种简洁而优越的方法,用于展示与过去的方法相比克拉姆率和SNR。读者可以理解这很方便。获得的双稳态系统的SNR表明,随机谐振(SR)可用于在绝热近似条件下从噪声实现从噪声到周期信号的能量转变。因此,SR可以增强输出信号的SNR。采用信号调制技术将大频率分量转换为小参数信号以满足绝热近似要求。此外,我们设计了调制器的模型。仿真结果表明,调制方法可以在双稳态系统中产生SR,并从强噪声背景中检测具有大参数的弱信号。

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