Yusoff, Nooraini and Ahmad, Farzana Kabir (2014) Spiking neural network with lateral inhibition for reward-based associative learning. In: Neural Information Processing. Lecture Notes in Computer Science, 8834 . Springer International Publishing, Switzerland, pp. 327-334. ISBN 978-3-319-12636-4
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In this paper we propose a lateral inhibitory spiking neural network for reward-based associative learning with correlation in spike patterns for conflicting responses. The network has random and sparse connectivity, and we introduce a lateral inhibition via an anatomical constraint and synapse reinforcement. The spiking dynamic follows the properties of Izhikevich spiking model. The learning involves association of a delayed stimulus pair to a response using reward modulated spike-time dependent plasticity (STDP). The proposed learning scheme has improved our initial work by allowing learning in a more dynamic and competitive environment.
Item Type: | Book Section |
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Uncontrolled Keywords: | Lateral inhibition. Spiking neural network. Associative Learning. Spike-time dependent plasticity. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | School of Computing |
Depositing User: | Dr. Nooraini Yusoff |
Date Deposited: | 04 Oct 2016 08:08 |
Last Modified: | 04 Oct 2016 08:08 |
URI: | https://repo.uum.edu.my/id/eprint/18762 |
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