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A Single-channel Mix Signal Separation Technique. The 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2007. Xiefeng Cheng Nianqiang Li Yuhan Cheng Zhengyu Chen. Jain-De Le TM. Outline. INTRODUCTION THE INDENPENDENT SUB-BAND FUNCTION MODEL
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A Single-channel Mix Signal Separation Technique The 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2007 Xiefeng Cheng Nianqiang Li Yuhan Cheng Zhengyu Chen. Jain-De LeTM
Outline • INTRODUCTION • THE INDENPENDENT SUB-BAND FUNCTION MODEL • A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE • SEPARATION EXPERIMENT • CONCLUSION
INTRODUCTION • Introduction of TEOAEs
A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE • The method of expanding the dimension of single signal • Single maxing model (two signal) • The signal x is chopped N segments x(t)=As(t) x(t)=a1s1(t)+a2s2(t) Formula A
A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE • Implement steps n=n+1 Procure sub-band functions Transform xn into a multi-dimensional Comparing Into a two-dimensional vector and separate Separate vector
A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE • Estimation of a1 and a2 • Estimation of a1 can be easily obtained by Formula A • Estimation of a2 • use posterior probability The log of maximizing posterior probability maximizes of a2
A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE • Solving where Φ2canbe obtained by the same form as that ofΦ1
SEPARATION EXPERIMENT Artifact Independent sub-band functions
SEPARATION EXPERIMENT To transform into a 4-dimensional vector Similitude coefficient (SC) and similitude phase diagram (SPD)
SEPARATION EXPERIMENT DNLR method Author’s method
CONCLUSION • Need only one signal • Similar coefficient is near to 1