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Almost All Noise Types Can Improve the Mutual Information of Threshold Neurons That Detect Subthreshold Signals

机译:几乎所有噪声类型都可以改善检测亚阈值信号的阈值神经元的相互信息

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Two new theorems show that small amounts of noise can increase the mutual information of threshold neurons that detect subthreshold signals. The first theorem shows that this "stochastic resonance" effect holds for all finite-variance noise probability density functions that obey a simple mean constraint that the user can control. The second theorem shows that this effect holds for all infinite-variance noise types in the broad class of stable distributions. Stable bell curves can model extremely impulsive noise environments. So the second theorem shows that this stochastic-resonance effect is robust against violent fluctuations in the additive noise process.
机译:两个新定理表明,少量噪声可以增加检测亚阈值信号的阈值神经元的相互信息。第一定理表明,这种“随机共振”效果适用于所有有限差异噪声概率密度函数,该函数遵守用户可以控制的简单平均约束。第二本定理表明,这种效果适用于广泛的稳定分布中的所有无限差异噪声类型。稳定的钟曲线可以模拟极其冲动的噪声环境。因此,第二定理表明,这种随机共振效应对添加剂噪声过程中的剧烈波动是鲁棒的。

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