引用本文: | 梁晓冰,刘希顺,刘安芝,等.微弱正弦信号在有噪声的FN神经元模型中的传输特性研究[J].国防科技大学学报,2008,30(2):78-82.[点击复制] |
LIANG Xiaobing,LIU Xishun,LIU Anzhi,et al.Transmission of Weak Sinusoidal Signal in the Noisy FN Neuron Model[J].Journal of National University of Defense Technology,2008,30(2):78-82[点击复制] |
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微弱正弦信号在有噪声的FN神经元模型中的传输特性研究 |
梁晓冰1, 刘希顺1, 刘安芝1, 王博亮2 |
(1.国防科技大学 电子科学与工程学院,湖南 长沙 410073;2.厦门大学 计算机科学系,福建 厦门 361005)
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摘要: |
长期以来弄清神经系统中的信号是如何传输的一直是广大研究人员努力的目标。针对一种被普遍研究的神经元简化模型——FitzHugh-nagumo(FN)模型,采用二阶随机龙格-库塔算法分析了该模型对加性噪声和微弱正弦信号的响应特性。时域和频域的统计参数表明适当强度的噪声有利于信号的传输,存在随机共振现象,即与噪声强度关联的输出信噪比曲线为倒钟形;另外值得关注的是,与正弦信号频率关联的输出信噪比曲线也为倒钟形,分析可见正弦信号的无量纲频率在区间0.2~0.8时模型的输出信噪比最大,表明该神经元模型有频率敏感性,即更易于检测到该范围内的弱信号。上述结果与生物学的发现是一致的,将有助于进一步揭示周期信号在神经元中的传输方法,建立更加准确的神经元数学模型。 |
关键词: FitzHugh-nagumo模型 神经元模型 噪声 随机共振 频率敏感性 |
DOI: |
投稿日期:2007-09-28 |
基金项目:国家自然科学基金资助项目(30770561) |
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Transmission of Weak Sinusoidal Signal in the Noisy FN Neuron Model |
LIANG Xiaobing1, LIU Xishun1, LIU Anzhi1, WANG Boliang2 |
(1.College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;2.Department of Computer Science, Xiamen Univ., Xiamen 361005, China)
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Abstract: |
To make out the signal processing of neuron and neural system, researchers have worked on it for scores of years. In this paper, the responses of FitzHugh-Nagumo (FN) neuron model, which is stimulated by additive Gaussian white noise and weak sinusoidal signal, is investigated via numerical simulations. The time and frequency domain results show that there is stochastic resonance and a dimensionless frequency sensitive range of 0.2-0.8. Thus the model can help to detect the sinusoidal signal. In addition, the frequency sensitivity coincides with the findings in biology and is beneficial to disclosing the secret in the signal transmission of neuron and neural system. |
Keywords: FitzHugh-nagumo model neuron model noise stochastic resonance frequency sensitivity |
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