Performance evaluation of the ICA-based adaptive filtering algorithm

Abstract

A novel finite impulse response (FIR) adaptive filter algorithm was proposed for system identification based on independent component analysis (ICA). It shows an excellent robustness for non-Gaussian disturbance. In this paper, we discuss various properties of this ICA-based adaptive filter algorithm, including the role of the scaling parameter, the local stability condition and a performance analysis by calculating the estimation error covariance matrix using the ordinary differential equation (ODE) approach.