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1、S121.2.,E-mail: 210046210003E-mail: : SFourierSSSSFourier:SEEG time-frequency analysis based on the improvedS-transformZHANG Shaobai1,HUANG Dandan21. Computer Department ,Nanjing University of Posts and Telecommunications ,nanjing,210046E-mail: 2. Computer Department ,Nanjing University of Posts and
2、 Telecommunications ,nanjing,210003E-mail: Abstract: S-transform, which is a combination of short-time Fourier transform and wavelet transform, has attract intensive interest inrecent years as an important tool to investigate non-stationary signal time-frequency distribution. S transform can be self
3、-improved bythe EEG characteristics to select a suitable mother wavelet. The improved S-transform will be used to analyze the time-frequency ofthe EEG characters. A comparison among the Short-time Fourier transform, wavelet transformation and the improved S-transformindicates that improved S-transfo
4、rm gives the best energy distribution in the time-frequency filed.Key Words: S transform; Time-frequency analysis; Electroencephalography(EEG); Wavelet Transform1EEGEEG2 SSCohenStSSSP(t, )2.1Stockwell R GSTFTSx (t ) L2 ( R)Sw(t,d )Sd*S61073515.WT ( , d ) =- x (t )x ( t )w ( t - ,d ) dt1978-1-4673-55
5、34-6/13/$31.00 c 2013 IEEE3410SST ( , f ) =- x ( t )f2e-22f 2-i 2 tS2342X (3NTX ()mNT)i 2 f 3Hn mNT MTfd =f -15Gn mNT MTw ( t,f ) =f2e-t 2 f 22e-i 2 tS46SnNT, jT345SS( t - )FourierffSSnNT, jTSFFTi 2 f S3SSTFTSfSSw( t,d )SSS2.2S3.1x(t)Sx(kT )MayerMorletHaarDaubechiesSymletsk =0,1,2N 1T2 STNT k =0nNTN
6、 1X ( ) = x(kT )e-i 2 nk NNT n m=0 NTS1 x(kT )mNT2n mNT MT2 2n2 NnnS10(5)FFTB Sn B n ( t )t0,10B10B SB f ( t ) =A f tf 1 ( tf ) - ( 2-tf ) 2 ( tf )A3.2 St 0 t 10,B678SSS2013 25th Chinese Control and Decision Conference (CCDC)3411( )t-e dtn + mST ( , f ) =e W ( , d ),eN = t X ( f ), jTf nn 1 N 1 n +
7、mX( )e 2 mS ( jT , ) =X ()G,e-i 2 mj1,0 t 1(t ) = ( x ) (t -x ) dt =t (t ) - ( 2-t ) SSWVD-i 2 ftB f ( t ) e - i 2 ft =A ftf 1 ( tf ) - ( 2-tf ) 2 ( tf)e - i 2 ft9STFTHeisenbergSTFTx ( t )S8S-i103SSTFTBSfSTFTA f4BSSBGabor3STTF11025HZ2001,206868014142SS2S3STFT34STFT24SS0.01s0.02s0.03s0.04s800HZ-1200H
8、ZSTFTS0.28140.53122.5321341222SSS2013 25th Chinese Control and Decision Conference (CCDC)SB f ( t ) eS(,f) = xt( ) Af (t-) f1(t-) f)-(2-(t-) f) 2(t-) f)e dt-2t55Ventosa S Simon C.The S-transform from a wavelet point ofviewJ.IEEE TransactionsSBon Signal Processing 200856(7):2771-2780.SSSTFT62007.S-D
9、.(MCE)7. S201137(2):217-219.J.S8.BJ.201128(11):214-254.9. S200626(2) 28-30.J.1234J 2004 8(1) 152-154.Schroder M Bogdan M,Hinterberger T et al. AutomatedEEG feature selection for brain computerinterfacesC/Proceedings of First International IEEEEMBS Conference on NeuralEngineering.S.I:IEEE,2003:626-629.J 2012,38(1) 21-37.SJ
