计算机工程与应用2011，Vol.47Issue(2)：112-114,142,4.DOI:10.3778/j.issn.1002-8331.2011.02.035
神经元网络模型的弱信号随机共振检测研究
Research on neuron network of weak signal based on stochastic resonance detection.
摘要
Abstract
Based on neuron network model coupling by FitzHugh-Nagumo(FHN) exciting cells,the paper researches on stochastic resonance detection mechanism of weak periodic signal in biology nerve system. Through the example of double layers FHN neuron network model formed by summing structure, the stochastic resonance mechanism of periodic signal response are investigated. The adopted evaluate criterions are signal-to-noise ratio and mutual information rate, combined with the output electric spike velocity and amplitude of nerve cells. Qualitative and quantitative analysis from these points of view are done for the double layers FHN neuron network model. Results indicate that,the stochastic resonance response of the double layers FHN neuron network is better than the single FHN neuron model, and has better stability, and can be effectively detected for input signal at a wider range of noise intensity.关键词
FitzHugh-Nagumo/神经元网络模型/随机共振Key words
FitzHugh-Nagumo/ neuron network model/ stochastic resonance分类
信息技术与安全科学引用本文复制引用
耿丽硕,范影乐..神经元网络模型的弱信号随机共振检测研究[J].计算机工程与应用,2011,47(2):112-114,142,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60872090). （the National Natural Science Foundation of China under Grant No.60872090）
