A new structure for adaptive signal processing with combined FIR & IIR filtering algorithms

Abstract

A new adaptive algorithm for system identification and adaptive signal processing has been proposed in this paper. The algorithm can be viewed as a combination of the output error type and the equation error type of identifier (i.e. a combination of IIR adaptive filter and FIR adaptive filter in signal processing application). It has been shown both mathematically and by computer simulation that the proposed algorithm can guarantee the globally asymptotical stability under certain regularity conditions on the distribution of signal modes. The transient behaviour of the algorithm is better than conventional output error type of identifier, especially in the case where the system model (signal model) has its eigenvalues on the unit circle. Under certain conditions on the system model (signal model), no moving average (MA) smoothing of the generalized error is needed for the strictly positive realness (SPR) conditions. It gives a reduced bias on the parameter estimate (compare to conventional adaptive FIR filter) when corresponding equation error is a bandlimited process.