A Hybrid Learning Algorithm Fusing STDP with GA based Explicit Delay Learning for Spiking Neurons

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Abstract

This paper presents a hybrid learning algorithmfor spiking neural networks (SNNs), referred to as an evolvablespiking neural network (ESNN) paradigm. The algorithmintegrates a supervised and unsupervised learning approach.The unsupervised approach exploits a Spike Timing DependentPlasticity (STDP) mechanism with explicit delay learningfor multiple connections between neurons. Supervision of thesynaptic delays and the excitatory/inhibitory connections isgoverned by a genetic algorithm (GA), while the STDP rule isfree to operate in its normal unsupervised manner. A spike trainencoding/decoding scheme is developed for the algorithm. Theapproach is validated by application to the Iris classificationproblem.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE
Pages632-637
Number of pages6
DOIs
Publication statusPublished (in print/issue) - Sept 2006
Event3rd IEEE International conference on Intelligent Systems, Westminster, London, September 06 -
Duration: 1 Sept 2006 → …

Conference

Conference3rd IEEE International conference on Intelligent Systems, Westminster, London, September 06
Period1/09/06 → …

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