Hopfield Networks, Simulated Annealing, and Chaotic Neural Networks

Ke-Lin Du () and M. N. S. Swamy
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Ke-Lin Du: Concordia University, Department of Electrical and Computer Engineering
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

Chapter Chapter 7 in Neural Networks and Statistical Learning, 2019, pp 173-200 from Springer

Abstract: Abstract Hopfield model is the most popular dynamic model. Simulated annealing, inspired by annealing in metallurgy, is a metaheuristic to approximate global optimization in a large search space. The annealing concept is widely used in the training of recurrent neural networks. Chaotic neural networks are recurrent neural networks introduced with chaotic dynamics. The cellular network is a generalization of the Hopfield network to a two- or higher dimensional array of cells. This chapter is dedicated to these topics. They are widely used for solving combinatorial optimization problems.

Date: 2019
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DOI: 10.1007/978-1-4471-7452-3_7

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