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摘要翻译：
阈上随机共振(SSR)是一种噪声增强的信号传输形式，它发生在包括模型神经元在内的独立噪声相同阈值非线性的并行阵列中。与大多数形式的随机共振不同，对任意大小的阈上随机输入信号的输出响应通过存在少量噪声而得到改善。本文考虑了SSR在大阵列尺寸限制下的信息传输性能。利用Shannon互信息与Fisher信息之间的关系，导出了最优性的充分条件，即信道容量。结果表明，当信号分布是由噪声分布形成的Jeffrey先验分布时，或当噪声分布与信号分布呈余弦关系时，容量是达到的。这些结果为先前在计算神经科学和电子学方面的工作提供了理论上的验证和依据。
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英文标题：
《Optimal stimulus and noise distributions for information transmission
via suprathreshold stochastic resonance》
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作者：
Mark D. McDonnell, Nigel G. Stocks and Derek Abbott
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最新提交年份：
2007
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分类信息：
一级分类：Physics 物理学
二级分类：Statistical Mechanics 统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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一级分类：Quantitative Biology 数量生物学
二级分类：Neurons and Cognition 神经元与认知
分类描述：Synapse, cortex, neuronal dynamics, neural network, sensorimotor control, behavior, attention
突触，皮层，神经元动力学，神经网络，感觉运动控制，行为，注意
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英文摘要：
Suprathreshold stochastic resonance (SSR) is a form of noise enhanced signal transmission that occurs in a parallel array of independently noisy identical threshold nonlinearities, including model neurons. Unlike most forms of stochastic resonance, the output response to suprathreshold random input signals of arbitrary magnitude is improved by the presence of even small amounts of noise. In this paper the information transmission performance of SSR in the limit of a large array size is considered. Using a relationship between Shannon's mutual information and Fisher information, a sufficient condition for optimality, i.e. channel capacity, is derived. It is shown that capacity is achieved when the signal distribution is Jeffrey's prior, as formed from the noise distribution, or when the noise distribution depends on the signal distribution via a cosine relationship. These results provide theoretical verification and justification for previous work in both computational neuroscience and electronics.
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PDF链接：
https://arxiv.org/pdf/704.0673
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