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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) In Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on 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:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
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)
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
2014-09-26 16:31:50
date last changed
2017-03-19 04:26:24
@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},
  year         = {2014},
}