In this paper, the expert system is introduced in order to detect and classify commonly power quality disturbances. This system is using learning vector quantization artificial neural networks. Clustering method named fuzzy c-mean is also utilized to initialize weight vector of first hidden layer. It can mitigate the disadvantage of LVQ ANN. The proposed system employs wavelet decomposition coefficients for extracting of deviated signals features. The determined feature vector is derived from Standard Deviation of 10-level decomposition detail coefficients. For the purpose of having efficient network, just 3 characteristic points among 10 points have been used, that leads to make networks training much

M_FILE\dcoffset.m
......\flicker.m
......\harmonic.m
......\impulsive.m
......\interruption.m
......\main3.m
......\noise.m
......\sag.m
......\swell.m
......\ten_level_std_detail.m
M_FILE

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