Comparison of Wiener filter solution by SVD with decompositions QR and QLP

Authors:
Edwirde Luiz Silva;Paulo Lisboa
Affiliations:
Departamento de Matemática e Estatística, Universidade Estadual da Paraíba - UEPB, Paraíba, Brasil;School of Computing and Mathematical Sciences, Liverpool John Moores University, Liverpool, England
Venue:
AIKED'07 Proceedings of the 6th Conference on 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases - Volume 6
Year:
2007

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Abstract

This paper presents a sequential decomposition of the data auto-correlation matrix using SVD, QR-method and QLP as pre-processors from the design of Wiener Filters. It is shown that this approach is effective for noise reduction by improving the SNR while reducing CPU time for a range of input signal lengths, filter length and noise variance. The theoretical and practical aspects of the proposed approach are introduced and compared to those obtained from simulation results.