"A reconfigurable SATLIN/SIGMOID/Gaussian/Triangular basis functions computation circuit"

Abstract

A CMOS Satlin/Sigmoid/Gaussian/triangular Basis functions computation circuit suitable for analog neural networks is proposed. The circuit can be configured to realize any of the four functions. The circuit can approximate these functions with relative root-mean-square error less than 1%. It is shown that the center, width, and peak amplitude of the dc transfer characteristic can be independently controlled. HSPICE simulation results using 0.18 mum CMOS process model parameters of TSMC technology are included