Generalized adaptive notch filters with frequency debiasing

Generalized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. Belonging to the class of causal adaptive filters, the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that this bias can be removed, or at least substantially reduced. The only price paid for the resulting improvement of the filter's tracking performance is in terms of a decision delay, which must be incorporated in the adaptive loop. Since decision delay is acceptable in many practical applications, the proposed bias/delay trade-off is an attractive alternative to the classical bias/variance compromise.