本帖最后由 wanglei_86 于 2010-5-12 10:48 编辑 : X m- p5 [) {. M) `& U& G( P4 A2 P* F: g$ u8 d7 d
欢迎大家一起研究S变换 . o$ U/ q+ D5 G% G& H* ~* A/ v5 g1 h! b$ n7 V' T8 d
A new approach to voltage sag detection based on wavelet transform.pdf, J/ f @' C) D- n
% G. T1 @& V: W% iAn expert system based on S-transform and neural network for automatic classification of power quality disturbances.pdf ( S. |/ H$ f% m3 { S( l) c9 Q 0 ?3 V5 G9 r$ K& p6 @/ Q) c! W, |7 rDetection and classification of power quality disturbances using S-transform and modular neural network.pdf , G! @0 g: ~1 y B+ W9 a3 a, r% d6 V# b; Y+ q
IEEE Recommended Practice for Monitoring Electric Power Quality.pdf+ j6 c4 z& I/ S }2 Z
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Localization of the Complex SpectrumThe S Transform.pdf z% a- J p+ b( `7 o: E
5 W d: }7 Z7 I. u0 a3 z) C$ q5 {Pattern recognition of power signal disturbances using S Transform and TT Transfom.pdf , ~9 j$ U( U2 S5 p1 H$ K' I/ I% Y- H+ i1 L
Power quality disturbance classification utilizing S-transform and binary feature matrix method.pdf: j! K' C' r; w' l/ v) P
) N! G/ L& y2 ^% [Rule based system for power quality disturbance classification incorporating S-transform features.pdf N8 _$ o. } s; N2 |0 S; P& {. ?7 _1 z0 E9 T! s* z. a- X
Short duration disturbance classifying based on S-transform maximum similarity.pdf
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发表于 2010-5-11 16:15:00
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