On the Effect of Cell Parameter Non-homogeneities in an Analog Parallel Architecture

The effect of non-homogeneities in cell parameters for a Cellular Neural Network (CNN) architecture consisting of linear cells locally connected within a specified neighborhood and able to exhibit pattern formation is investigated. The results are an extension for another architecture of Turing pattern formation in nonhomogeneous two-grid CNN's and are based on a continuity theorem about the dependence of polynomial roots on their coefficients.