Quantization of filter bank frame expansions through moving horizon optimization

Authors:
Daniel E. Quevedo;Helmut Bölcskei;Graham C. Goodwin
Affiliations:
School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, NSW, Australia;Communication Technology Laboratory, ETH Zurich, Zurich, Switzerland;School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, NSW, Australia
Venue:
IEEE Transactions on Signal Processing
Year:
2009

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Abstract

This paper describes a novel approach to quantization in oversampled filter banks. The new technique is based on moving horizon optimization, does not rely on an additive white noise quantization model and allows stability to be explicitly enforced in the associated nonlinear feedback loop. Moreover, the quantization structure proposed here includes ΣΔ and linear predictive subband quantizers as a special case and, in general, out-performs them.