FIR–IIR adaptive filters hybrid combination. Issue 7 (1st March 2014) - Ferro, H.F.; Chamon, L.F.O.; Lopes, C.G.
Abstract : To enhance the performance in IIR system identification scenarios, a hybrid combination of FIR and IIR adaptive filters (AFs) via a supervisor that senses which one is performing best is proposed. The FIR‐LMS AF is short, providing fast and robust convergence, whereas the IIR‐LMS AF is slow but accurate. The stagnation effect caused by the different convergence rates is tackled through cyclic weight transfers FIR → IIR, which also ensure good tracking properties. A design technique for the transfers cycle length is proposed, providing good convergence while keeping computational cost low.