Wavelet based feature extraction for classification of power quality disturbances
نویسندگان
چکیده
منابع مشابه
Wavelet based feature extraction for classification of Power Quality Disturbances
The detection and classification of power quality disturbances in power systems are important tasks in monitoring and protection of power system network. Most of the power system disturbances are non stationary and transitory in nature and new tools are being used nowadays for the analysis of power quality disturbances. This paper presents a wavelet based feature extraction method for the detec...
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The emergence of power quality as a topical issue in power systems in the 1990s largely coincides with the huge advancements achieved in the computing technology and information theory. This unsurprisingly has spurred the development of more sophisticated instruments for measuring power quality disturbances and the use of new methods in processing and analyzing the measurements. Fourier theory ...
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Speech is one of the vital signals of acoustic classification. Speech recognition is also significant and very well known of audio processing. Speech contains very important frequency information of human being. The features of Audio, especially speech signal may be extracted using FFT (Fast Fourier Transform) and Wavelet to detect the frequency information of the signal. But it is difficult to...
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ژورنال
عنوان ژورنال: Renewable Energy and Power Quality Journal
سال: 2011
ISSN: 2172-038X,2172-038X
DOI: 10.24084/repqj09.340