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Nonuniform Subband Adaptive Filtering With Critical Sampling

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2 Author(s)
Petraglia, M.R. ; State Univ. of Rio de Janeiro, Rio de Janeiro ; Batalheiro, P.B.

Adaptive subband structures have been proposed with the objective of increasing the convergence speed and/or reducing the computational complexity of conventional adaptive algorithms, mainly for applications that require a large number of adaptive coefficients. In this paper, we present a nonuniform subband structure with critical sampling, which is capable of modeling an arbitrary finite-impulse response (FIR) system with reduced aliasing. A least-mean-square (LMS)-type adaptation algorithm with normalized step sizes, which works at the lowest downsampling rate and minimizes the average of the subband squared errors, is derived for the proposed structure. A convergence analysis of the adaptation algorithm is presented, from which its convergence rate and steady-state mean-square error can be estimated.

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Signal Processing, IEEE Transactions on  (Volume:56 ,  Issue: 2 )