本帖最后由 wanglei_86 于 2010-5-12 10:48 编辑 - o2 H- Y; h0 b# n7 u8 {
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欢迎大家一起研究S变换" ]; `8 y" N y2 Q: A A
; _" R' H' h6 n+ h9 Y8 |1 gA new approach to voltage sag detection based on wavelet transform.pdf ! r5 v& F; T5 ^% ~& F 1 g4 i8 R& h/ T' \7 K; DAn expert system based on S-transform and neural network for automatic classification of power quality disturbances.pdf& K' K, |. n1 h4 |* t# X; G
% W" R* v' U4 ^/ N/ g! mDetection and classification of power quality disturbances using S-transform and modular neural network.pdf9 G8 @! M& ~5 c2 u4 D; a+ y2 Z
( U! A+ A4 G6 n! c+ a a2 CIEEE Recommended Practice for Monitoring Electric Power Quality.pdf) @& h m7 d0 {0 {$ t( C# J
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Localization of the Complex SpectrumThe S Transform.pdf ) {/ |/ ?# K$ o5 |/ [. T* m0 D * g* s+ u- X# ]$ RPattern recognition of power signal disturbances using S Transform and TT Transfom.pdf' T6 \$ B4 X& u& c1 F
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Power quality disturbance classification utilizing S-transform and binary feature matrix method.pdf # E; d9 K& c5 u- x6 e. V 5 P1 s, f% D0 y9 zRule based system for power quality disturbance classification incorporating S-transform features.pdf, k0 _- V: M$ _+ ?- y) U9 W
/ f4 \; [9 n; {( {) }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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