Block-Recursive IAA-based Spectral Estimates with Missing Samples using data interpolation
Glentis, George ; Jakobsson, Andreas LU
and Angelopoulos, Kostas
(2014)
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)
p.350-354
- Abstract
- In this work, we examine a computationally efficient block-updating scheme for estimating the spectral content of signals with missing samples. The work is an extension of our recent single-sample data interpolation updating of the Iterative Adaptive Approach (IAA), being reformulated to incorporate blocks of samples. The proposed implementation offers a substantial complexity reduction as compared to earlier presented updating schemes, without sacrificing the quality of the resulting spectral estimates more than marginally (if at all).
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4645561
- author
- Glentis, George
; Jakobsson, Andreas
LU
and Angelopoulos, Kostas
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)
- conference location
- Florence, Italy
- conference dates
- 2014-05-04 - 2014-05-09
- external identifiers
-
- scopus:84905240735
- ISBN
- 978-1-4799-2892-7
- DOI
- 10.1109/ICASSP.2014.6853616
- language
- English
- LU publication?
- yes
- id
- 6bd87f73-96b9-41b6-8482-e3442899eeb0 (old id 4645561)
- alternative location
- http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6853616
- date added to LUP
- 2016-04-04 11:41:42
- date last changed
- 2022-03-23 17:59:21
@inproceedings{6bd87f73-96b9-41b6-8482-e3442899eeb0,
abstract = {{In this work, we examine a computationally efficient block-updating scheme for estimating the spectral content of signals with missing samples. The work is an extension of our recent single-sample data interpolation updating of the Iterative Adaptive Approach (IAA), being reformulated to incorporate blocks of samples. The proposed implementation offers a substantial complexity reduction as compared to earlier presented updating schemes, without sacrificing the quality of the resulting spectral estimates more than marginally (if at all).}},
author = {{Glentis, George and Jakobsson, Andreas and Angelopoulos, Kostas}},
booktitle = {{Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on}},
isbn = {{978-1-4799-2892-7}},
language = {{eng}},
pages = {{350--354}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Block-Recursive IAA-based Spectral Estimates with Missing Samples using data interpolation}},
url = {{http://dx.doi.org/10.1109/ICASSP.2014.6853616}},
doi = {{10.1109/ICASSP.2014.6853616}},
year = {{2014}},
}