Generalized adaptive notch filters

The problem of identification/tracking of quasi-periodically varying systems is considered. This problem is a generalization, to the system case, of a classical signal processing task of either elimination or extraction of nonstationary sinusoidal signals buried in noise. The proposed solution is based on the exponentially weighted basis function (EWBF) approach. First, the global EWBF algorithm is derived and its decomposed, parallel-form and cascade-form variants, are described. Then the frequency-adaptive versions of both schemes are obtained using the recursive prediction error method. In the (special) signal processing case the paper offers new attractive solutions to the problem of adaptive notch filtering.