Triplet-based spike timing dependent plasticity (TSTDP) modeling using VHDL-AMS

被引：4

作者：

Shahim-Aeen, Afsaneh ^{[1
]}

Karimi, Gholamreza ^{[1
]}

机构：

[1] Razi Univ, Fac Engn, Dept Elect Engn, Kermanshah 67149, Iran

来源：

NEUROCOMPUTING | 2015年 / 149卷

关键词：

Synaptic plasticity; Spike timing dependent plasticity (STDP); Rate-based plasticity; Neuromorphic engineering; VHDL-AMS; SYNAPTIC PLASTICITY; SILICON NEURON;

D O I：

10.1016/j.neucom.2014.08.050

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Spike Timing Dependent Plasticity is one of the synaptic plasticity rules that plays an important role in learning and memory in the brain. There are two rules to describe STDP; the conventional one is pair-based STDP (PSTDP) and the other one is triplet-based STDP (TSTDP) that is a powerful synaptic plasticity rule and acts beyond the classical rule. Although PSTDP fails to reproduce some of the experimental observations. TSTDP is capable of reproducing them. In this paper, a VHDL-AMS based TSTDP model is presented which exhibits the behavioral model of triplet-based spike timing dependent plasticity. The proposed model is simulated using Ansoft Simplorer. This model has similar results to the mentioned experimental observations and is capable of being employed in different analog or digital implementations of neuromorphic systems. (c) 2014 Elsevier B.V. All rights reserved.

引用

页码：1440 / 1444

页数：5

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