Pulse-type hardware model with STDP-like learning

被引：0

作者：

Otaki, Mitsuhiko ^{[1
]}

Ohwada, Ken ^{[1
]}

Saeki, Katsutoshi ^{[2
]}

Sekine, Yoshifumi ^{[2
]}

机构：

[1] Department of Electronic Engineering, School of Science and Technology, Nihon University, 1-8-14,Kanda Surugadai, Chivoda-ku. Tokyo 101-8308, Japan

[2] Department of Electronics and Computer Science, College of Science and Technology, Nihon University, 7-24-1 Narashinodai, Funabashi. Chiba 274-8501, Japan

来源：

IEEJ Transactions on Electronics, Information and Systems | 2014年 / 134卷 / 10期

关键词：

The synaptic plasticity has important role of learning function of neurons. Reportedly STDP (Spike Timing Dependent synaptic Plasticity) is generated between inputs of pre-synaptic neurons and backpropagation of the active potential from dendrites of post-synaptic neuron; as revealed by physiological experiments. Hie purpose of our research is construction of the hardware learning model with STDP-like learning rules. In this paper; we study on a Pulse-type Hardware Neuron Model (hereafter P-HNM) focused on a dendrite in order to make a Pulse-type Hardware Neural Network. As a result; we show that the P-HNM can mimic STDP characteristics of biological neuron. © 2014 The Institute of Electrical Engineers of Japan;

D O I：

10.1541/ieejeiss.134.1485

中图分类号：

学科分类号：

摘要：

引用

页码：1485 / 1491

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