Image filtering in a CMOS analog CNN

Abstract

A compact low-power CMOS analog circuit implementation of a Cellular Neural Network which uses continuously programmable weight values has been presented recently. Now the operation of this full signal range CNN in image filtering is verified through simulation. A learning tool comprising a friendly graphical interface and the center of mass learning algorithm has been developed, which made it possible to determine optimal coefficients for CNN application in image filtering. Circuit simulations of low-pass and high-pass filters have been accomplished with satisfactory results.