Abstract
Cellular neural networks (CNN) are described by large systems of locally coupled nonlinear differential equations. In most applications the connectivity are specified through space-invariant templates. As far as the dynamic behavior is concerned, CNNs can be divided in two main classes: stable CNNs, with the property that each trajectory (with exception of a set of measure zero) converges towards an equilibrium point; unstable CNNs, that exhibit at least one attractor, that is not a stable equilibrium point. Due to their complex dynamics, only a few methods for template design have been so far proposed. We propose a rigorous design algorithm for stable CNNs and we identify the class of templates to which such an algorithm can be applied.
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