Learning algorithm for total least-squares adaptive signal processing

A new adaptive learning algorithm, called the constrained anti-Hebbian algorithm, is presented. This algorithm is optimal in the total least-squares sense, simple to use, and can be applied to on-line adaptive FIR and IIR filtering directly. Simulation results confirm that the proposed algorithm provides significantly better performance over the least mean-squares (LMS) and recursive least-squares (RLS) algorithms.