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基于IF模型阈值神经元的随机共振 被引量:2

Stochastic resonance of an integrate-and-fire neuron model with threshold
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摘要 文章基于带阈值的积分放电模型,研究了神经元在背景噪声和周期信号驱动下的随机共振现象。利用镜像法得到峰电位时间间隔(interspike interval,简称ISI)的概率密度函数,通过数值积分得到平均ISI,数值模拟表明,ISI概率密度函数的峰值与噪声强度的关系曲线是非单调的,平均ISI关于信号频率的演化是非单调的。结果表明,在背景噪声和周期信号驱动下,动作电位的发放确实存在随机共振现象。 Stochastic resonance(SR) of an integrate-and-fire neuron model with threshold subjected to white background noise and periodic input signal is investigated. The probability density function of interspike interval(ISI) and the mean ISI are obtained by the methods of mirror image and numerical integration respectively. Numerical simulation shows that the relational curve between the peak height of probability dengity function and the noise intensity is nonmonotonous, so is between the mean ISI and the input frequency. The results show that SR occurs during the neuronal spiking driven by back- ground noise and periodic input signal.
出处 《合肥工业大学学报(自然科学版)》 CAS CSCD 北大核心 2010年第6期939-942,954,共5页 Journal of Hefei University of Technology:Natural Science
基金 合肥工业大学博士学位人员专项基金资助项目(GDBJ2009-007)
关键词 随机共振 噪声 积分放电模型 ISI密度函数 平均ISI stochastic resonance(SR) noise integrate-and-fire model density function of interspike interval(ISI) mean interspike interval(ISI)
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同被引文献15

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