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

  • Authors:

  • Jun Liu;Jian Wu;Zhengguo Lou;Guang Li

  • Affiliations:

  • Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, P.R. China;Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, P.R. China;Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, P.R. China;Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, P.R. China

  • Venue:
  • ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
  • Year:
  • 2006

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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.