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.
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Lynch, S. (2010). Neural Networks. In: Dynamical Systems with Applications using Maple¿. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4605-9_18
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DOI: https://doi.org/10.1007/978-0-8176-4605-9_18
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Online ISBN: 978-0-8176-4605-9
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