A hybrid differential evolution algorithm for parameter tuning of evolving spiking neural network

In this paper, differential evolution (DE) has been utilised to solve the problem of tuning the parameters of evolving spiking neural network (ESNN) manually. As ESNN is sensitive to its parameters as other models, optimal integration of parameters leads to better classification accuracy. A hybrid d...

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Bibliographic Details
Main Authors: Saleh, Abdulrazak Yahya, Shamsuddin, Siti Mariyam, Abdull Hamed, Haza Nuzly
Format: Article
Published: Inderscience Publishers 2017
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Online Access:http://eprints.utm.my/id/eprint/97057/
http://dx.doi.org/10.1504/IJCVR.2017.081231
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Institution: Universiti Teknologi Malaysia
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