An effective approach to adaptive IIR filtering

An approach to adaptive IIR filtering based on a pseudo-linear regression and a QR matrix decomposition is developed. The algorithm has proved to be stable and has good convergence properties if the unknown system satisfies the strictly positive real condition. The derivation of the algorithm is straightforward and the computational complexity is less than the computational complexity of the IIR-RPE algorithm. Simulation results of system identification with synthetic and real world data are shown comparing the algorithm with the IIR-RPE and the IIR-LMS algorithm.