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Title

Noise reduction design of perfect reconstruction oversampled filter banks

Author(s)

Chai, Li;  Zhang, Jingxin;  Zhang, Cishen;  Mosca, Edoardo

Abstract

This paper studies the noise reduction design problem for oversampled filter banks (FBs) with perfect reconstruction (PR) constraint. Both the optimal design and worst case design are considered, where the former method caters for the noise with known power spectral density (PSD) and the latter one for the noise with unknown PSD. Explicit formulae involving only algebraic Riccati equation and matrix manipulations are provided for the general (IIR or FIR) oversampled PR FBs.

Publication type

Conference paper

Source

Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), Toulouse, France, 14-19 May 2006, Vol. 3, pp. 229-232

Publication year

2006

Keyword(s)

Adaptive filters;  Constraint theory;  Filter banks;  Image reconstruction;  Matrix manipulations;  Noise abatement;  Oversampled filter banks;  Perfect reconstruction (PR) constraint;  Power spectral density;  Problem solving;  Riccati equations

Publisher

IEEE

ISSN

1520-6149 (series ISSN)

ISBN

9781424404698, 142440469X

Publisher URL

http://dx.doi.org/10.1109/ICASSP.2006.1660632

Copyright

Copyright © 2006 IEEE. The published version of the paper is reproduced here in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Full text

Peer reviewed