IEICE Electronics Express
Online ISSN : 1349-2543
LETTER
STDP implementation using memristive nanodevice in CMOS-Nano neuromorphic networks
Ahmad AfifiAhmad AyatollahiFarshid Raissi
Author information
JOURNALS FREE ACCESS

2009 Volume 6 Issue 3 Pages 148-153

Details
Abstract

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.

Information related to the author
© 2009 by The Institute of Electronics, Information and Communication Engineers
Previous article Next article
feedback
Top