Efficient time-recursive implementation of matched filterbank spectral. estimators
(2005) In IEEE Transactions on Circuits and Systems Part 1: Fundamental Theory and Applications 52(3). p.516-521- Abstract
- In this paper, we present a computationally efficient sliding window time updating of the Capon and amplitude and phase,estimation (APES) matched filterbank spectral estimators based on the time-variant displacement structure of the data covariance matrix. The presented algorithm forms a natural extension of the most computationally efficient algorithm to date, and offers a significant computational gain as compared to the computational complexity associated with the batch re-evaluation of the spectral estimates for each time-update. Furthermore, via simulations, the algorithm is found to be numerically superior to the time-updated spectral estimate formed from directly updating the data covariance matrix.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1216102
- author
- Alty, Stephen ; Jakobsson, Andreas LU and Larsson, Erik G.
- publishing date
- 2005
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- adaptive filters, computational complexity, covariance matrices, iterative methods, spectrum analysis, time-varying systems, APES
- in
- IEEE Transactions on Circuits and Systems Part 1: Fundamental Theory and Applications
- volume
- 52
- issue
- 3
- pages
- 516 - 521
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:16344385309
- ISSN
- 1057-7122
- DOI
- 10.1109/TCSI.2004.842876
- language
- English
- LU publication?
- no
- id
- 69652895-1473-4c10-bb74-9a963d6b1e34 (old id 1216102)
- date added to LUP
- 2016-04-04 09:45:42
- date last changed
- 2022-01-29 19:26:36
@article{69652895-1473-4c10-bb74-9a963d6b1e34, abstract = {{In this paper, we present a computationally efficient sliding window time updating of the Capon and amplitude and phase,estimation (APES) matched filterbank spectral estimators based on the time-variant displacement structure of the data covariance matrix. The presented algorithm forms a natural extension of the most computationally efficient algorithm to date, and offers a significant computational gain as compared to the computational complexity associated with the batch re-evaluation of the spectral estimates for each time-update. Furthermore, via simulations, the algorithm is found to be numerically superior to the time-updated spectral estimate formed from directly updating the data covariance matrix.}}, author = {{Alty, Stephen and Jakobsson, Andreas and Larsson, Erik G.}}, issn = {{1057-7122}}, keywords = {{adaptive filters; computational complexity; covariance matrices; iterative methods; spectrum analysis; time-varying systems; APES}}, language = {{eng}}, number = {{3}}, pages = {{516--521}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Transactions on Circuits and Systems Part 1: Fundamental Theory and Applications}}, title = {{Efficient time-recursive implementation of matched filterbank spectral. estimators}}, url = {{http://dx.doi.org/10.1109/TCSI.2004.842876}}, doi = {{10.1109/TCSI.2004.842876}}, volume = {{52}}, year = {{2005}}, }