Diamond in multi-layer cellular neural networks

Abstract

This investigation considers the complexity of output spaces of multi-layer cellular neural networks. Let B be a set of admissible local output patterns coupled with input and let (B) over tilde be the set of admissible output patterns extracting from B. Since topological entropy is an indicator for investigating the complexity of spaces, we study the topological entropy of output spaces Y-U and Y which are induced by B and (B) over tilde, respectively. A system has a diamond if h(Y-U)not equal h(Y). Necessary and sufficient conditions for the existence of diamond are demonstrated separately. Furthermore, numerical experiments exhibit some novel phenomena.