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Adelaide Research and Scholarship
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Electrical and Electronic Engineering Publications
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2440/74610
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| Type: | Conference paper |
| Title: | Efficient design of triplet based spike-timing dependent plasticity |
| Author: | Rahimi Azghadi, Seyed Mostafa Al-Sarawi, Said Fares Khalil Iannella, Nicolangelo Abbott, Derek |
| Citation: | Proceedings of the 2012 IEEE World Congress on Computational Intelligence, held in Brisbane, Queensland, 10-15 June, 2012; pp.1-7 |
| Publisher: | IEEE |
| Issue Date: | 2012 |
| ISBN: | 9781467314886
 9781467314893 |
| ISSN: | 2161-4393 |
| Conference Name: | IEEE World Congress on Computational Intelligence (2012 : Brisbane, QLD) WCCI 2012 |
| School/Discipline: | School of Electrical and Electronic Engineering |
Statement of Responsibility: | Mostafa Rahimi Azghadi, Said Al-Sarawi, Nicolangelo Iannella and Derek Abbott |
| Abstract: | to play an important role in learning and the formation of computational function in the brain. The classical model of STDP which considers the timing between pairs of pre-synaptic and post-synaptic spikes (p-STDP) is incapable of reproducing synaptic weight changes similar to those seen in biological experiments which investigate the effect of either higher order spike trains (e.g. triplet and quadruplet of spikes) [1]–[3], or, simultaneous effect of the rate and timing of spike pairs [4] on synaptic plasticity. In this paper, we firstly investigate synaptic weight changes using a p-STDP circuit [5] and show how it fails to reproduce the mentioned complex biological experiments. We then present a new STDP VLSI circuit which acts based on the timing among triplets of spikes (t-STDP) that is able to reproduce all the mentioned experimental results. We believe that our new STDP VLSI circuit improves upon previous circuits, whose learning capacity exceeds current designs due to its capability of mimicking the outcomes of biological experiments more closely; thus plays a significant role in future VLSI implementation of neuromorphic systems. |
| Keywords: | Communication; networking and broadcasting; components; circuits; devices and systems; computing and processing (hardware/software); engineered materials; dielectrics and plasmas; fields, waves and electronmagnetics; robotics and control systems |
| Rights: | © Copyright 2012 IEEE - All rights reserved. |
| RMID: | 0020121686 |
| DOI: | 10.1109/IJCNN.2012.6252820 |
| Appears in Collections: | Electrical and Electronic Engineering Publications
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| View citing articles in: | Google Scholar Scopus
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