Stochastic resonance and self-tuning: a simple threshold system.
Stochastic resonance and self-tuning: a simple threshold system.
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DOI：
10.1103/physreve.79.061121
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发表时间：
2009-06
期刊：
影响因子：
--
通讯作者：
T. Kondo;T. Munakata
中科院分区：
文献类型：
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作者：
T. Kondo;T. Munakata
在信息处理的框架中，随机共振是一种现象，在这种现象中，适当（非零）强度的噪声可以显著增加信息从输入信号到输出信号的传递。SR的最低要求通常是输入信号、非线性和噪声，以及测量信息传递效率的量器。我们研究了一个简单的阈值系统，并提出了一种系统参数的自适应机制，如阈值和噪声强度（即温度），这些参数在正常的SR设置中保持固定。我们的重点放在由这种适应引起的参数动态上，我们称之为自调谐（ST），以及这种动态如何修改或改变SR图像的信息处理效率。我们采用互信息和信噪比作为阈值系统性能的衡量标准。这些量分别用解析法和模拟法计算。温度的ST导致温度的振荡时间变化，其平均值位于SR设置中性能最大化的温度附近。阈值的ST被证明可以提高弱噪声区域的性能。
To put it in the framework of information processing, stochastic resonance (SR) is a phenomenon in which the transfer of information from input to output signals can be significantly increased by noise with appropriate (nonzero) intensity. The minimum requirements for SR are generally input signals, nonlinearity, and noise, in addition to a quantifier to measure the efficiency of information transfer. We study a simple threshold system and propose an adaptation mechanism for system parameters, such as a threshold and noise intensity (i.e., temperature), which are held fixed in a normal SR setting. Our emphasis is put on parameter dynamics induced by this adaptation, which we call self-tuning (ST), and on how this dynamics modifies or changes the SR picture with respect to information processing efficiency. As a measure for performance of the threshold system we take mutual information and the signal-to-noise ratio. These quantities are calculated by an analytical method and by a simulational one. ST of temperature results in oscillatory time variation in temperature with its average located around the temperature at which performance is maximized in the SR setting. ST of a threshold turns out to improve performance in the weak noise region.