Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary data
The Multisensor Time–FrequencySignal Processing (MTFSP) Matlab package is an analysis tool for multichannel non-stationary signals collected from an array of sensors. By combining array signal processing for non-stationary signals and multichannel high resolution time–frequency methods, MTFSP enable...
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doaj-54a43926278b4c22b806c215555c70a12020-11-25T00:44:07ZengElsevierSoftwareX2352-71102018-07-0185358Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary dataBoualem Boashash0Abdeldjalil Aïssa-El-Bey1Mohammad F. Al-Sa’d2Corresponding author (formerly with Qatar University).; The University of Queensland, Centre for Clinical Research, Brisbane, Australia; IMT Atlantique, UMR CNRS 6285 Lab-STICC, UBL, F-29238 Brest, FranceThe University of Queensland, Centre for Clinical Research, Brisbane, Australia; IMT Atlantique, UMR CNRS 6285 Lab-STICC, UBL, F-29238 Brest, FranceThe University of Queensland, Centre for Clinical Research, Brisbane, Australia; IMT Atlantique, UMR CNRS 6285 Lab-STICC, UBL, F-29238 Brest, FranceThe Multisensor Time–FrequencySignal Processing (MTFSP) Matlab package is an analysis tool for multichannel non-stationary signals collected from an array of sensors. By combining array signal processing for non-stationary signals and multichannel high resolution time–frequency methods, MTFSP enables applications such as cross-channel causality relationships, automated component separation and direction of arrival estimation, using multisensor time–frequency distributions (MTFDs). MTFSP can address old and new applications such as: abnormality detection in biomedical signals, source localization in wireless communications or condition monitoring and fault detection in industrial plants. It allows e.g. the reproduction of the results presented in Boashash and Aïssa-El-Bey (in press) [2]. Keywords: Multisensor time–frequency analysis, Direction of arrival, Automated component separation, Blind source separation, Non-stationary array processing, Cross-channel causality analysishttp://www.sciencedirect.com/science/article/pii/S2352711017300687 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Boualem Boashash Abdeldjalil Aïssa-El-Bey Mohammad F. Al-Sa’d |
spellingShingle |
Boualem Boashash Abdeldjalil Aïssa-El-Bey Mohammad F. Al-Sa’d Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary data SoftwareX |
author_facet |
Boualem Boashash Abdeldjalil Aïssa-El-Bey Mohammad F. Al-Sa’d |
author_sort |
Boualem Boashash |
title |
Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary data |
title_short |
Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary data |
title_full |
Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary data |
title_fullStr |
Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary data |
title_full_unstemmed |
Multisensor Time–Frequency Signal Processing MATLAB package: An analysis tool for multichannel non-stationary data |
title_sort |
multisensor time–frequency signal processing matlab package: an analysis tool for multichannel non-stationary data |
publisher |
Elsevier |
series |
SoftwareX |
issn |
2352-7110 |
publishDate |
2018-07-01 |
description |
The Multisensor Time–FrequencySignal Processing (MTFSP) Matlab package is an analysis tool for multichannel non-stationary signals collected from an array of sensors. By combining array signal processing for non-stationary signals and multichannel high resolution time–frequency methods, MTFSP enables applications such as cross-channel causality relationships, automated component separation and direction of arrival estimation, using multisensor time–frequency distributions (MTFDs). MTFSP can address old and new applications such as: abnormality detection in biomedical signals, source localization in wireless communications or condition monitoring and fault detection in industrial plants. It allows e.g. the reproduction of the results presented in Boashash and Aïssa-El-Bey (in press) [2]. Keywords: Multisensor time–frequency analysis, Direction of arrival, Automated component separation, Blind source separation, Non-stationary array processing, Cross-channel causality analysis |
url |
http://www.sciencedirect.com/science/article/pii/S2352711017300687 |
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