Neural Networks

Stephen Lynch
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Stephen Lynch: Manchester Metropolitan University School of Computing, Mathematics & Digital Technology, Department of Computing and Mathematics

Chapter Chapter 18 in Dynamical Systems with Applications using MATLAB®, 2014, pp 377-411 from Springer

Abstract: Abstract Aims and Objectives • To provide a brief historical background to neural networks. • To investigate simple neural network architectures. • To consider applications in the real world. • To present working MATLAB program files for some neural networks. • To introduce neurodynamics. On completion of this chapter the reader should be able to • use the generalized delta learning rule with backpropagation of errors to train a network; • determine the stability of Hopfield networks using a suitable Lyapunov function; • use the Hopfield network as an associative memory; • study the dynamics of a neuromodule in terms of bistability, chaos, periodicity, quasiperiodicity, and chaos control.

Keywords: Bifurcation Diagram; Less Mean Square; Synaptic Weight; Chaos Control; Hopfield Network (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-06820-6_18

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DOI: 10.1007/978-3-319-06820-6_18

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