本帖最后由 wanglei_86 于 2010-5-12 10:48 编辑 0 Z) I) w1 R% e w / z: R0 p, ]- s o! e5 g欢迎大家一起研究S变换5 L' s! M, o0 X) }$ l4 I( z/ [3 ~
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A new approach to voltage sag detection based on wavelet transform.pdf( O. q' s% t: {6 B; y6 `6 w% E
( m* y3 w4 s7 {$ f( n7 O2 zAn expert system based on S-transform and neural network for automatic classification of power quality disturbances.pdf0 @$ K+ F, G* d. S, J; d! g5 ~ a
3 Q+ H) d: l$ sDetection and classification of power quality disturbances using S-transform and modular neural network.pdf+ U6 o1 j. I8 ]6 V5 k& O% \0 T
% g# _ G( w. U1 Z& UIEEE Recommended Practice for Monitoring Electric Power Quality.pdf ; X" p- \/ ]4 O7 w2 q ^2 @ ; X; M7 e( l/ N' K; yLocalization of the Complex SpectrumThe S Transform.pdf+ ?4 P9 R- k9 Q! T) D0 H, x* ~
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Pattern recognition of power signal disturbances using S Transform and TT Transfom.pdf 2 M4 d, ^( ?; m0 A6 o / f6 F7 `$ H1 ~' F4 tPower quality disturbance classification utilizing S-transform and binary feature matrix method.pdf8 Q i7 Y3 F/ w! O% L6 w) P0 M8 Q
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Rule based system for power quality disturbance classification incorporating S-transform features.pdf + R4 y G3 b( \( ^ " k Q1 `2 t( V2 lShort 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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