Synthesis of Bipolar Associative Memories Based on Cellular Neural Networks with Two-dimensional Space-invariant Templates

Abstract

In this paper, a design procedure is presented for synthesizing associative memories based on cellular neural networks with two-dimensional space-invariant templates. The theoretical analysis herein guarantees that the desired memory patterns are stored as asymptotically stable equilibrium points. In addition, it is shown that procedure herein can ensure the designed input matrix to be obtained by using space-invariant cloning templates. Hence, it is very convenient for one to design cellular neural networks for associative desired memory patterns effectively.