Analog CMOS implementation of cellular neural networks

Abstract

The analog CMOS circuit realization of cellular neural networks with transconductance elements is presented. This realization can be easily adapted to various types of applications in image processing just by choosing the appropriate transconductance parameters according to the predetermined coefficients. The effectiveness of the designed circuits for connected component detection is shown by HSPICE simulations. For “fixed function” cellular neural network circuits the number of transistors are reduced further by using multi-input transconductance elements.