An analog Gaussian generator circuit for radial basis function neural networks with non-volatile center storage

A BiCMOS analog circuit that computes a Gaussian function suitable for use in radial basis function neural networks is proposed. The circuit accepts multiple voltage inputs and stores the basis function center in a set of nonvolatile floating gate memory cells. The design is well suited for adaptive networks that use on-chip learning. Experimental results of the circuit are shown.