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Stochastic resonance in two simple compare-and-fire models

机译:两个简单的“比较并发射”模型中的随机共振

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摘要

Two neural models are analysed and shown to exhibit the stochastic resonance effect. Namely, they respond to an underthreshold sinusoidal signal with an output signal whose signal-to-noise ratio (SNR) firstly increases then decreases as the intensity of noise affecting the system increases. The resonance curves are determined, analytically for the first and simplest model and by a synthetic method for the second one, and the respective resonant behaviours are illustrated and interpreted.
机译:对两个神经模型进行了分析,并显示出随机共振效应。即,它们以输出信号响应阈值以下的正弦信号,该信号的信噪比(SNR)首先增大,然后随着影响系统的噪声强度的增加而减小。对于第一个和最简单的模型,通过分析确定共振曲线,对于第二个模型,通过合成方法确定共振曲线,并说明和解释相应的共振行为。

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