STDP implementation using memristive nanodevice in CMOS-Nano neuromorphic networks

被引：38

作者：

Afifi, Ahmad ^{[1
]}

Ayatollahi, Ahmad ^{[1
]}

Raissi, Farshid ^{[2
]}

机构：

[1] Iran Univ Sci & Technol, EE Dept, Tehran, Iran

[2] KN Toosi Univ Technol, ECE Dept, Tehran, Iran

来源：

IEICE ELECTRONICS EXPRESS | 2009年 / 6卷 / 03期

关键词：

CMOL; memristive; neuromorphic networks; STDP learning;

D O I：

10.1587/elex.6.148

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Implementation of a correlation-based learning rule, Spike-Timing- Dependent-Plasticity (STDP), for asynchronous neuromorphic networks is demonstrated using 'memristive' nanodevice. STDP is performed using locally available information at the specific moment of time, for which mapping to crossbar-based CMOS-Nano architectures, such as CMOS-MOLecular (CMOL), is done rather easily. The learning method is dynamic and online in which the synaptic weights are modified based on neural activity. The performance of the proposed method is analyzed for specifically shaped spikes and simulation results are provided for a synapse with STDP properties.

引用

页码：148 / 153

页数：6

共 12 条

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