Afifi, A. and Ayatollahi, A. and Raissi, F. (2009) STDP implementation using memristive nanodevice in CMOS-Nano neuromorphic networks. IEICE ELECTRONICS EXPRESS, 6 (3). pp. 148-153. ISSN 1349-2543
Full text is not hosted in this archive but may be available via the Official URL, or by requesting a copy from the corresponding author.
Official URL: http://www.jstage.jst.go.jp/article/elex/6/3/6_148...
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.
| Item Type: | Article |
|---|---|
| Subjects: | Physical Science > Nanophysics Physical Science > Nano objects Material Science > Nanochemistry Material Science > Nanostructured materials |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Physics Faculty of Engineering, Science and Mathematics > School of Chemistry |
| ID Code: | 7320 |
| Deposited By: | JNCASR |
| Deposited On: | 28 Oct 2009 09:40 |
| Last Modified: | 28 Oct 2009 09:40 |
Repository Staff Only: item control page
