Optimal Noise Reduction in Oversampled PR Filter Banks

Author

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

Author_Institution

Key Lab. of Metall. Equip. & Control, Wuhan Univ. of Sci. & Technol., Wuhan, China

Volume

57

Issue

10

fYear

2009

Firstpage

3844

Lastpage

3857

Abstract

This paper studies the optimal noise reduction problem for oversampled filter banks (FBs) with perfect reconstruction (PR) constraint. Both the optimal design and worst case design are considered, where the former caters for the noise with known power spectral density (PSD) and the latter for the noise with unknown PSD. State-space based explicit formulae involving only algebraic Riccati equation and matrix manipulations are provided for the general (IIR or FIR) oversampled PR FBs, and the relations between different cases are analyzed and revealed. Extensive numerical examples are provided to illustrate the proposed design methods and to show their effectiveness.

Keywords

Riccati equations; channel bank filters; matrix algebra; numerical analysis; signal denoising; signal reconstruction; signal sampling; algebraic Riccati equation; matrix manipulations; numerical examples; optimal design; optimal noise reduction; oversampled PR filter banks; perfect reconstruction constraint; power spectral density; state-space based explicit formulae; worst case design; Dual frame; noise reduction; oversampled filter banks; perfect reconstruction; state-space approach;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/TSP.2009.2024280

Filename

5061645