An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology

Abstract

This paper describes an analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a Gaussian function obtained through the characteristic of the bipolar differential pair. The Gaussian parameters (gain, center and width) are changed with a programmable current source. Results obtained with PSPICE software are shown.