Time-Recursive IAA Spectral Estimation
Glentis, George and Jakobsson, Andreas LU
(2011)
In IEEE Signal Processing Letters
18(2).
p.111-114
- Abstract
- This letter presents computationally efficient time-updating algorithms of the recent Iterative Adaptive Approach (IAA) spectral estimation technique. By exploiting the inherently low displacement rank, together with the development of suitable Gohberg-Semencul (GS) representations, and the use of data dependent trigonometric polynomials, the proposed time-recursive IAA algorithm offers a reduction of the necessary computational complexity with at least one order of magnitude. The resulting complexity can also be reduced further by allowing for approximate solutions. Numerical simulations together with theoretical complexity measures illustrate the achieved performance gain.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1761202
- author
- Glentis, George
and Jakobsson, Andreas
LU
- organization
- publishing date
- 2011
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Adaptive spectral estimation, iterative adaptive approach (IAA), fast algorithms
- in
- IEEE Signal Processing Letters
- volume
- 18
- issue
- 2
- pages
- 111 - 114
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- wos:000285843400003
- scopus:78650991750
- ISSN
- 1070-9908
- DOI
- 10.1109/LSP.2010.2099113
- language
- English
- LU publication?
- yes
- id
- 7943aa69-b990-4c9c-844c-49bfb513eda5 (old id 1761202)
- date added to LUP
- 2016-04-04 10:38:10
- date last changed
- 2022-04-16 02:06:37
@article{7943aa69-b990-4c9c-844c-49bfb513eda5,
abstract = {{This letter presents computationally efficient time-updating algorithms of the recent Iterative Adaptive Approach (IAA) spectral estimation technique. By exploiting the inherently low displacement rank, together with the development of suitable Gohberg-Semencul (GS) representations, and the use of data dependent trigonometric polynomials, the proposed time-recursive IAA algorithm offers a reduction of the necessary computational complexity with at least one order of magnitude. The resulting complexity can also be reduced further by allowing for approximate solutions. Numerical simulations together with theoretical complexity measures illustrate the achieved performance gain.}},
author = {{Glentis, George and Jakobsson, Andreas}},
issn = {{1070-9908}},
keywords = {{Adaptive spectral estimation; iterative adaptive approach (IAA); fast algorithms}},
language = {{eng}},
number = {{2}},
pages = {{111--114}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Signal Processing Letters}},
title = {{Time-Recursive IAA Spectral Estimation}},
url = {{http://dx.doi.org/10.1109/LSP.2010.2099113}},
doi = {{10.1109/LSP.2010.2099113}},
volume = {{18}},
year = {{2011}},
}