Imperial College London
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ProfessorDaniloMandic

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Machine Intelligence
 
 
 
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Contact

 

+44 (0)20 7594 6271d.mandic Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

813Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Brajović:2021:10.1109/IT51528.2021.9390140,
author = {Brajovi, M and Stankovi, I and Dakovi, M and Mandic, DP and Stankovi, L},
doi = {10.1109/IT51528.2021.9390140},
title = {On the Number of Channels in Multicomponent Nonstationary Noisy Signal Decomposition},
url = {http://dx.doi.org/10.1109/IT51528.2021.9390140},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - If acquired using multiple sensors, non-stationary multicomponent signals can be decomposed into individual components by exploiting interdependences of signals from different channels. Earlier, we have proposed a decomposition approach being able to extract individual non-stationary signal components even in the challenging cases when their domains of support overlap in the time, frequency or joint time-frequency (TF) domains. The approach is based upon the eigenvalue analysis of the multichannel autocorrelation matrix and minimizations of concentration measures calculated using TF representations. In this paper, we investigate the influence of the number of sensors (channels) and external noise variance to the outcome of the decomposition process.
AU  - Brajovi,M
AU  - Stankovi,I
AU  - Dakovi,M
AU  - Mandic,DP
AU  - Stankovi,L
DO  - 10.1109/IT51528.2021.9390140
PY  - 2021///
TI  - On the Number of Channels in Multicomponent Nonstationary Noisy Signal Decomposition
UR  - http://dx.doi.org/10.1109/IT51528.2021.9390140
ER  -
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