Neural Networks

  • Stephen Lynch

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 Maple program worksheets 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.


Neural Network Hide Layer Lyapunov Function Bifurcation Diagram Synaptic Weight 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Birkhäuser Boston 2010

Authors and Affiliations

  1. 1.Department of Computing and MathematicsManchester Metropolitan UniversityManchesterUK

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