A new class of subband adaptive filter using alias-free maximally decimated DFT-bank

Conventional subband adaptive filters (ADFs) using filter banks have shown degradation in performance because of the nonideal nature of the filters. A frequency sampling filter (FSF) bank is proposed which enables identification of an unknown system. An efficient implementation of the FSF bank using the discrete Fourier transform (DFT) is illustrated and a class of ADFs using the FSF bank that is based on the frequency sampling theorem is proposed. This technique enables subband adaptive processing without the degradation effect of both the aliasing and cross terms, even if critical subsampling is chosen.<
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