Fast Parameter Selection Algorithm for Linear Parametric Filters

Akira TANAKA
Masaaki MIYAKOSHI

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E90-A    No.12    pp.2952-2956
Publication Date: 2007/12/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e90-a.12.2952
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Digital Signal Processing
Keyword: 
linear filtering,  joint diagonalization,  parametric linear filter,  parameter selection,  Moore-Penrose generalized inverse matrix,  

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Summary: 
A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.

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