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Classification of Nonstationary Power Signals using Support Vector Machine and Extreme Learning Machine

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IJCA Proceedings on International Conference on Emergent Trends in Computing and Communication
© 2015 by IJCA Journal
ETCC 2015 - Number 2
Year of Publication: 2015
Authors:
Itishree Panda
Satyasis Mishra

Itishree Panda and Satyasis Mishra. Article: Classification of Nonstationary Power Signals using Support Vector Machine and Extreme Learning Machine. IJCA Proceedings on International Conference on Emergent Trends in Computing and Communication ETCC 2015(2):22-26, September 2015. Full text available. BibTeX

@article{key:article,
	author = {Itishree Panda and Satyasis Mishra},
	title = {Article: Classification of Nonstationary Power Signals using Support Vector Machine and Extreme Learning Machine},
	journal = {IJCA Proceedings on International Conference on Emergent Trends in Computing and Communication},
	year = {2015},
	volume = {ETCC 2015},
	number = {2},
	pages = {22-26},
	month = {September},
	note = {Full text available}
}

Abstract

The classification of nonstationary signals in a noisy environment is a difficult task. In this paper a modified version of S-Transform technique has been proposed for classification of power signal disturbances. The S-Transform is a signal processing technique which is used for visual localization, detection, pattern classification. S-Transform has good ability in gathering high frequency signals and suppressing the lower frequency signal. The S-Transform has been used to extract features from the nonstationary power disturbance signals. The extracted features are fed as the input support vector machine classifier for power signal disturbance pattern classification. To enhance the pattern classification accuracy the extreme learning classifier has been proposed and comparison results has been presented

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