When are two multi-layer cellular neural networks the same?

Ban, Jung-Chao; Chang, Chih-Hung · Neural Netw · 2016

basic_science · Level V

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Abstract

This paper aims to characterize whether a multi-layer cellular neural network is of deep architecture; namely, when can an n-layer cellular neural network be replaced by an m-layer cellular neural network for m<n yet still preserve the same output phenomena? From a mathematical point of view, such characterization involves investigating whether the topological structure of two (or multiple) layers is conjugate. A decision procedure that addresses the necessary and sufficient condition for the topological conjugacy between two layers in a network is revealed.

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