Piecewise-Linear Approximation of Any Smooth Output Function on the Cellular Neural Network

Abstract

The Cellular Neural Network Universal Machine (CNNUM)[7] is a novel hardware architecture which make use of complex spatio-temporal dynamics performed in the Cellular Neural Network (CNN)[1] for solving real-time image processing tasks. Actual VLSI chip prototypes [6] have the limitation of performing a fixed piecewise-linear (PWL) saturation output function. In this work, a novel algorithm for emulating a piecewise-linear (PWL) approximation of any nonlinear output function on the CNNUM VLSI chip is presented.