Analysis of associative memories based on cellular neural networks with value-varying templates

Abstract

ABSTRACTIn many research literatures, the dynamical behaviour of cellular neural networks (CNNs) is simplified by using cloning template. However, the flaws of cloning template are obvious, because the correlation between weights of cells in CNNs is enhanced. In order to overcome the shortcomings of cloning template, value-varying templates can be used in CNNs. In this paper, associative memories based on CNNs with value-varying templates are investigated. A criterion about stability of CNNs is presented. Then, the problem about obtaining parameters of CNNs can be translated into a problem of solving linear equations for each cell. A design procedure of associative memories is given by our theories and methods. From the procedure, the parameters of CNNs can be obtained. Finally, three examples are used to demonstrate the effectiveness of our theories and methods. And the results show that success rate of associative memories is higher than previous methods.