On frequency weighting in autoregressive spectral estimation
2005 (English)In: IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2005, 245-248 p.Conference paper (Refereed)
This paper treats the problem of approximating a complex stochastic process in a given frequency region by an estimated autoregressive (AR) model. Two frequency domain approaches are discussed: a weighted frequency domain maximum likelihood method and a prefiltered covariance extension method based on the theory of Lindquist and co-workers. It is shown that these two approaches are very closely related and can both be formulated as convex optimization problems. An examples illustrating the methods and the effect of prefiltering/weighting is provided. The results show that these methods are capable of tuning the AR model fit to a specified frequency region.
Place, publisher, year, edition, pages
2005. 245-248 p.
, International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Signal Processing Control Engineering
IdentifiersURN: urn:nbn:se:kth:diva-26580DOI: 10.1109/ICASSP.2005.1415991ISI: 000229404203062ScopusID: 2-s2.0-33646807509ISBN: 0-7803-8874-7OAI: oai:DiVA.org:kth-26580DiVA: diva2:379145
30th IEEE International Conference on Acoustics, Speech, and Signal Processing Philadelphia, PA, MAR 19-23, 2005
FunderSwedish Research Council
QC 201012172010-12-172010-11-252016-06-22Bibliographically approved