A GENERALIZED LEAKY INTEGRATE-AND-FIRE NEURON MODEL WITH FAST IMPLEMENTATION METHOD

被引：33
|
作者：
Wang, Zhenzhong [1 ]
Guo, Lilin [1 ]
Adjouadi, Malek [1 ]
机构：
[1] Florida Int Univ, Ctr Adv Technol & Educ, Miami, FL 33174 USA
来源：
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS | 2014年 / 24卷 / 05期
基金：
美国国家科学基金会;
关键词：
Exponential moving average; Hodgkin-Huxley model; leaky integrate-and-fire; neuron model; SPIKING; NETWORKS; ADAPTATION;
D O I：
10.1142/S0129065714400048
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This study introduces a new Generalized Leaky Integrate-and-Fire (GLIF) neuron model with variable leaking resistor and bias current in order to reproduce accurately the membrane voltage dynamics of a biological neuron. The accuracy of this model is ensured by adjusting its parameters to the statistical properties of the Hodgkin-Huxley model outputs; while the speed is enhanced by introducing a Generalized Exponential Moving Average method that converts the parameterized kernel functions into pre-calculated lookup tables based on an analytic solution of the dynamic equations of the GLIF model.
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页数：15
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