An empirical study towards efficient learning in artificial neural networks by neuronal diversity

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An empirical study towards efficient learning in artificial neural networks by neuronal diversity

Artificial Neural Networks (ANN) are biologically inspired algorithms, and it is natural that it continues to inspire research in artificial neural networks. From the recent breakthrough of deep learning to the wake-sleep training routine, all have a common source of drawing inspiration: biology. Th...

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Bibliographic Details
Main Author:	Adamu, Abdullahi Shuaibu
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2016
Subjects:	neuroevolution artificial neural networks biologically-inspired algorithms transfer function optimisation
Online Access:	https://eprints.nottingham.ac.uk/33799/

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