Minimum classification error using time-frequency analysis

C. Breakenridge; M. Mesbah

doi:10.1109/ISSPIT.2003.1341221

Minimum classification error using time-frequency analysis

C. Breakenridge, M. Mesbah

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

2 Citations (Scopus)

Abstract

For certain classes of signals, such as time varying signals, classical classification algorithms are not suitable. Hence, time-frequency based techniques are employed for classification of these types of signals. In this paper we propose data-driven time frequency representations kernel optimization, that leads to the minimum classification error (MCE) for nonstationary signal classification. Our central issue is to determine the optimal kernel parameters and best distance measure to achieve the MCE performance measure. The minimum classification error achievable using optimized kernels is investigated for two types of nonstationary signals; namely simulated chirp signals and real-life newborn EEG signals. For the EEG signals a classification error as low as 4.6% was achieved.

Original language	English
Title of host publication	Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	717-720
Number of pages	4
ISBN (Electronic)	0780382927, 9780780382923
DOIs	https://doi.org/10.1109/ISSPIT.2003.1341221
Publication status	Published - 2003
Externally published	Yes
Event	3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003 - Darmstadt, Germany Duration: Dec 14 2003 → Dec 17 2003

Publication series

Name	Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003

Other

Other	3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
Country/Territory	Germany
City	Darmstadt
Period	12/14/03 → 12/17/03

Keywords

Algorithm design and analysis
Chirp
Electroencephalography
Kernel
Optimization methods
Pediatrics
Signal analysis
Signal processing algorithms
Testing
Time frequency analysis

ASJC Scopus subject areas

Signal Processing

Access to Document

10.1109/ISSPIT.2003.1341221

Cite this

Breakenridge, C., & Mesbah, M. (2003). Minimum classification error using time-frequency analysis. In Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003 (pp. 717-720). Article 1341221 (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSPIT.2003.1341221

Minimum classification error using time-frequency analysis. / Breakenridge, C.; Mesbah, M.
Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003. Institute of Electrical and Electronics Engineers Inc., 2003. p. 717-720 1341221 (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003).

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

Breakenridge, C & Mesbah, M 2003, Minimum classification error using time-frequency analysis. in Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003., 1341221, Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003, Institute of Electrical and Electronics Engineers Inc., pp. 717-720, 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003, Darmstadt, Germany, 12/14/03. https://doi.org/10.1109/ISSPIT.2003.1341221

Breakenridge C, Mesbah M. Minimum classification error using time-frequency analysis. In Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003. Institute of Electrical and Electronics Engineers Inc. 2003. p. 717-720. 1341221. (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003). doi: 10.1109/ISSPIT.2003.1341221

Breakenridge, C. ; Mesbah, M. / Minimum classification error using time-frequency analysis. Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003. Institute of Electrical and Electronics Engineers Inc., 2003. pp. 717-720 (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003).

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abstract = "For certain classes of signals, such as time varying signals, classical classification algorithms are not suitable. Hence, time-frequency based techniques are employed for classification of these types of signals. In this paper we propose data-driven time frequency representations kernel optimization, that leads to the minimum classification error (MCE) for nonstationary signal classification. Our central issue is to determine the optimal kernel parameters and best distance measure to achieve the MCE performance measure. The minimum classification error achievable using optimized kernels is investigated for two types of nonstationary signals; namely simulated chirp signals and real-life newborn EEG signals. For the EEG signals a classification error as low as 4.6% was achieved.",

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Minimum classification error using time-frequency analysis

Abstract

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Keywords

ASJC Scopus subject areas

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