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A convex optimization approach to arma(n,m) model design from covariance and cepstral data
KTH, Superseded Departments, Mathematics.
2004 (English)In: SIAM Journal of Control and Optimization, ISSN 0363-0129, E-ISSN 1095-7138, Vol. 43, no 3, 1011-1036 p.Article in journal (Refereed) Published
Abstract [en]

Methods for determining ARMA(n, m) filters from covariance and cepstral estimates are proposed. In [C. I. Byrnes, P. Enqvist, and A. Lindquist, SIAM J. Control Optim., 41 ( 2002), pp. 23-59], we have shown that an ARMA( n, n) model determines and is uniquely determined by a window r(0), r(1),..., r(n) of covariance lags and c(1), c(2),..., c(n) of cepstral lags. This unique model can be determined from a convex optimization problem which was shown to be the dual of a maximum entropy problem. In this paper, generalizations of this problem are analyzed. Problems with covariance lags r(0), r(1),..., r(n) and cepstral lags c(1), c(2),..., c(m) of different lengths are considered, and by considering different combinations of covariances, cepstral parameters, poles, and zeros, it is shown that only zeros and covariances give a parameterization that is consistent with generic data. However, the main contribution of this paper is a regularization of the optimization problems that is proposed in order to handle generic data. For the covariance and cepstral problem, if the data does not correspond to a system of desired order, solutions with zeros on the boundary occur and the cepstral coefficients are not interpolated exactly. In order to achieve strictly minimum phase filters for estimated covariance and cepstral data, a barrier-like term is introduced to the optimization problem. This term is chosen so that convexity is maintained and so that the unique solution will still interpolate the covariances but only approximate the cepstral lags. Furthermore, the solution will depend analytically on the covariance and cepstral data, which provides robustness, and the barrier term increases the entropy of the solution.

Place, publisher, year, edition, pages
2004. Vol. 43, no 3, 1011-1036 p.
Keyword [en]
cepstrum, covariance, ARMA, entropy, convex optimization
National Category
Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-13176DOI: 10.1137/S0363012901399751ISI: 000225642700013Scopus ID: 2-s2.0-19944383824OAI: oai:DiVA.org:kth-13176DiVA: diva2:321484
Note
QC 20100601Available from: 2010-06-01 Created: 2010-06-01 Last updated: 2017-12-12Bibliographically approved
In thesis
1. Spectral Estimation by Geometric, Topological and Optimization Methods
Open this publication in new window or tab >>Spectral Estimation by Geometric, Topological and Optimization Methods
2001 (English)Doctoral thesis, comprehensive summary (Other scientific)
Place, publisher, year, edition, pages
Stockholm: KTH, 2001. xii, 32 p.
Series
Trita-MAT, ISSN 1401-2286 ; 01-OS-03
Keyword
Spectral Estimation, ARMA models, Covariance analysis, Cepstral analysis, Markov parameters, Global analysis, Convex Optimization, Continuation methods, Entropy maximization
National Category
Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-3118 (URN)
Public defence
2001-04-06, 00:00 (English)
Note
QC 20100601Available from: 2001-03-29 Created: 2001-03-29 Last updated: 2010-06-01Bibliographically approved

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