Stochastic resonance enhancing detectability of weak signal by neuronal networks model for receiver

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Abstract

Stochastic resonance phenomenon in a biological sensory system has been studied through signal detection theories and psychophysical experiments. There is a conflict between the real experiments and the traditional signal detection theory for stochastic resonance because the latter treats the receiver as linear model. This paper presents a two-layer summing network of Hodgkin-Huxley (HH) neurons and a summing network of threshold devices to model the receiver, respectively. The simulation results indicate that the relevant index of signal detectability exhibit the stochastic resonance characteristics. © Springer-Verlag Berlin Heidelberg 2006.

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Liu, J., Wu, J., Lou, Z., & Li, G. (2006). Stochastic resonance enhancing detectability of weak signal by neuronal networks model for receiver. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3971 LNCS, pp. 15–20). Springer Verlag. https://doi.org/10.1007/11759966_3

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