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软阈值随机共振

Soft threshold stochastic resonance.

作者信息

Greenwood Priscilla E, Müller Ursula U, Ward Lawrence M

机构信息

Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287-1804, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Nov;70(5 Pt 1):051110. doi: 10.1103/PhysRevE.70.051110. Epub 2004 Nov 30.

Abstract

Soft thresholds are ubiquitous in living organisms, in particular in mechanisms of neurons and of neural networks such as sensory systems. Which soft threshold functions produce (threshold) stochastic resonance remains a question. The answer may depend on the information measure used. We argue that Fisher information about signal parameters is an attractive measure of information transmission across soft thresholds. We illustrate how the pattern of information changes as a signal moves across a soft threshold. For some signals this pattern is much the same whether Fisher information or signal-to-noise ratio is used as a measure of information transmission. Noninvertibility of the threshold function, rather than its steepness, is important for stochastic resonance measured by Fisher information.

摘要

软阈值在生物有机体中无处不在,尤其是在神经元和神经网络(如感觉系统)的机制中。哪些软阈值函数会产生(阈值)随机共振仍是一个问题。答案可能取决于所使用的信息度量。我们认为,关于信号参数的费希尔信息是衡量跨软阈值信息传输的一个有吸引力的度量。我们说明了当信号跨越软阈值时信息模式是如何变化的。对于某些信号,无论使用费希尔信息还是信噪比作为信息传输的度量,这种模式大致相同。对于用费希尔信息度量的随机共振而言,阈值函数的不可逆性而非其陡峭程度才是重要的。

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