Paper Info
Title
Block-recursive IAA-based spectral estimates with missing samples using data interpolation
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).
Year
DOI
Venue
2014
10.1109/ICASSP.2014.6853616
Acoustics, Speech and Signal Processing
Keywords
Field
DocType
interpolation,iterative methods,recursive estimation,signal sampling,spectral analysis,block-recursive IAA-based spectral estimates,complexity reduction,computationally efficient block-updating scheme,iterative adaptive approach,missing samples,signal spectral content,single-sample data interpolation,Iterative Adaptive Approach (IAA),Spectrum estimation theory and methods,fast algorithms
Mathematical optimization,Pattern recognition,Computer science,Interpolation,Reduction (complexity),Artificial intelligence,Recursion
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
12
3
Name
Order
Citations
PageRank
George-Othon Glentis112913.59
Andreas Jakobsson240943.32
Kostas Angelopoulos383.58