Analysis and design of associative memories based on cellular neural networks with space-invariant cloning templates

This paper presents a new design procedure for the synthesis of associative memories based on cellular neural networks characterized by input and output matrices obtained based on cloning templates by solving a set of inequalities. The design parameters are few even though the dimension of patterns may be very high. The design procedure enables heteroassociative or autoassociative memories to be synthesized with assured global exponential stability and feeding retrieval probes via external inputs rather than initial conditions. Two specific examples are shown to illustrate the applicability of the methodology.