Circuit implementation of digitally programmable transconductance amplifier in analog simulation of reaction-diffusion neural model

被引：0

作者：

Sun, Miao ^{[1
]}

He, Xing ^{[1
]}

Wang, Tiancai ^{[1
]}

Tan, Jie ^{[1
]}

Xia, Dawen ^{[2
]}

机构：

[1] Southwest Univ, Sch Elect & Informat Engn, Chongqing 400715, Peoples R China

[2] Guizhou Minzu Univ, Sch Informat Engn, Guiyang 550025, Peoples R China

来源：

NEUROCOMPUTING | 2017年 / 227卷

关键词：

Reaction-diffusion equation; Neural network; Circuit implementation; EXPONENTIAL STABILITY; NETWORKS; DELAYS; SYNCHRONIZATION;

D O I：

10.1016/j.neucom.2016.07.062

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with circuit implementation in reaction-diffusion neuron model. Firstly, in order to realize easily, one obtains the equivalent form by discretization of this neuron model. In the frame of discrete model, every parameter can be represented by the basic circuit component. Then the digital programmable transconductance amplifier (DPTA) is designed to realize the digitally function in circuit. In addition, the DPTA is applied to realize two activation functions and the simulation results are verified in Multisim.

引用

页码：74 / 81

页数：8

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