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A study on the parameters of bistable stochastic resonance systems and adaptive stochastic resonance

机译:双稳态随机共振系统和自适应随机共振的参数研究

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Noise can improve the signal-to-noise ratio of many nonlinear dynamical systems. This ''stochastic resonance" (SR) effect occurs in a wide range of physical and biological systems, and also occurs in engineering systems in signal processing, communications, and control. Most SR studies assume the signal and noise properties are known. To overcome this limitation, we give a type of adaptive stochastic resonance. This paper present a novel approach for investigating the relationships among the parameters of a bistable SR system, based on the characteristics of digital simulations. Using this approach, we can obtain the system's responses with varying parameters and these responses are consistent with experimental results. As a direct application, a system can be moved into the SR condition by conveniently changing its structural parameters, even when it is forced by an unknown periodic signal embedded in a white Gaussian noise with unknown statistical properties.
机译:噪声可以改善许多非线性动力学系统的信噪比。这种“随机共振”(SR)效应发生在广泛的物理和生物系统中,还发生在信号处理,通信和控制的工程系统中,大多数SR研究都假定信号和噪声特性是已知的。针对这种局限性,我们给出了一种自适应随机共振的方法,本文基于数字仿真的特点,提出了一种研究双稳态SR系统各参数之间关系的新颖方法,利用该方法可以获得系统的响应。作为直接应用,即使直接受到嵌入高斯白噪声中的未知周期信号的强迫,系统也可以通过方便地更改其结构参数而进入SR条件。统计属性。

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