Adaptive IIR digital filtering using an analog neural network

A novel neural network method for adaptive IIR digital filtering is proposed. Based on the linear prediction principle and the observable data at the IIR filter input and output prior to the current iteration time k, an analog neural network is used to estimate the filter coefficients of the next iteration time k+1. Computer simulation results are given which indicate our method has several advantages over the conventional LMS algorithm in stability and convergence.