Dynamics of Neural Networks with Delay: Attractors and Content-Addressable Memory

In the design of a neural network, either for biological modeling, cognitive simulation, numerical computation or engineering applications, it is important to describe the dynamics of the network. The success in this area in the early 1980’s was one of the main sources for the resurgence of interest in neural networks, and the current progress towards understanding neural dynamics has been part of exhaustive efforts to lay down a solid theoretical foundation for this fast growing theory and for the applications of neural networks.

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