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Stochastic resonance in coupled small-world neural networks

Yu Hai-Tao Wang Jiang Liu Chen Che Yan-Qiu Deng Bin Wei Xi-Le

Stochastic resonance in coupled small-world neural networks

Yu Hai-Tao, Wang Jiang, Liu Chen, Che Yan-Qiu, Deng Bin, Wei Xi-Le
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  • Received Date:  01 May 2011
  • Accepted Date:  08 August 2011
  • Published Online:  20 March 2012

Stochastic resonance in coupled small-world neural networks

    Corresponding author: Wang Jiang, jiangwang@tju.edu.cn
  • 1. School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant No. 61072012) and the Young Scientists Fund of the National Natural Science Foundation of China (Grant Nos. 50907044, 60901035).

Abstract: Noise exists widely in biological neural systems, and plays an important role in system functions. A complex neural network, which contains several small-world subnetworks, is constructed based on a two-dimensional neural map. The phenomenon of stochastic resonance induced by Gaussian white noise is studied. It is found that only with an appropriate noise, can the frequency response of the network to input signal reach a peak value. Moreover, network structure has an important influence on the stochastic resonance of the neural system. With a fixed coupling strength, there exists an optimal local small-world topology, which can offer the best frequency response of the network.

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