Classification of time-varying signals using time-frequency atoms

Peter Wellig; George S. Moschytz

Classification of time-varying signals using time-frequency atoms

Peter Wellig, George S. Moschytz

Swiss Federal Institute of Technology Zurich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

Extracting relevant features from signals is a key element in classification of signals, e.g., for the decomposition of electromyograms (EMG signals). In this paper, we present an algorithm which uses time-frequency dictionaries and adaptively selects a small number of discriminant time-frequency atoms. Using our method, simulations show reduced misclassification rates compared to commonly-used linear classifiers.

Original language	English
Title of host publication	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages	953
Number of pages	1
State	Published - 1999
Externally published	Yes
Event	Proceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS) - Atlanta, GA, USA Duration: 13 Oct 1999 → 16 Oct 1999

Publication series

Name	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	2
ISSN (Print)	0589-1019

Conference

Conference	Proceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
City	Atlanta, GA, USA
Period	13/10/99 → 16/10/99

Cite this

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title = "Classification of time-varying signals using time-frequency atoms",

abstract = "Extracting relevant features from signals is a key element in classification of signals, e.g., for the decomposition of electromyograms (EMG signals). In this paper, we present an algorithm which uses time-frequency dictionaries and adaptively selects a small number of discriminant time-frequency atoms. Using our method, simulations show reduced misclassification rates compared to commonly-used linear classifiers.",

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Wellig, P & Moschytz, GS 1999, Classification of time-varying signals using time-frequency atoms. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, vol. 2, pp. 953, Proceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS), Atlanta, GA, USA, 13/10/99.

Classification of time-varying signals using time-frequency atoms. / Wellig, Peter; Moschytz, George S.
Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 1999. p. 953 (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Classification of time-varying signals using time-frequency atoms

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