A SIMPLE NEURON NETWORK BASED ON HEBB'S RULE

Gui-Qing Zhang (), Zi Yu, Qiu-Ying Yang and Tian-Lun Chen
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Gui-Qing Zhang: Department of Physics, Nanjing Forestry University, Nanjing 210037, P. R. China
Zi Yu: Department of Physics, Nanjing Forestry University, Nanjing 210037, P. R. China
Qiu-Ying Yang: College of Physics and Electronic Engineering, Changshu Institute of Technology, Changshu 215500, P. R. China
Tian-Lun Chen: Department of Physics, Nankai University, Tianjin 300071, P. R. China

International Journal of Modern Physics C (IJMPC), 2011, vol. 22, issue 07, 755-763

Abstract: A weighted mechanism in neural networks is studied. This paper focuses on the neuron's behaviors in an area of brain. Our model could regenerate the power-law behaviors and finite size effects of neural avalanche. The probability density functions (PDFs) for the neural avalanche size differing at different times (lattice size) have fat tails with aq-Gaussian shape and the same parameter value ofqin the thermodynamical limit. Above two kinds of behaviors show that our neural model can well present self-organized critical behavior. The robustness of PDFs shows the stability of self-organized criticality. Meanwhile, the avalanche scaling relation of the waiting time has been found.

Keywords: Self-organized criticality; neural model; average membrane potential; scaling relation; 05.65.+b; 45.70.Ht (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1142/S0129183111016609

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