CNN models of complex pattern formation in excitable media

The paper presents the nonlinear discrete-time cellular neural networks as a model of excitable media. It can be considered as a CNN solution of a reaction-diffusion equation. This approach adapts the cellular automation of Gerhardt and Schuster (1989) to the CNN paradigm. It is shown that a large variety of complex patterns (including various types of spiral waves) can be efficiently obtained by the proper choice of the model parameters.