Cellular neural networks and zeta functions

Abstract

This talk is concerned with zeta functions of two-dimensional shifts of finite type. The zeta function is an important invariant, which combines information of all periodic patterns. The zeta function can be explicitly expressed as a reciprocal of an infinite product of polynomials by patterns generation approaches. The methods can apply to two-dimensional cellular neural networks.