1

A Single-channel Mix Signal

Separation Technique

Jain-De LeTM

The 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2007

Xiefeng Cheng Nianqiang Li Yuhan Cheng Zhengyu Chen.

2

Outline• INTRODUCTION

• THE INDENPENDENT SUB-BAND FUNCTION MODEL

• A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE

• SEPARATION EXPERIMENT

• CONCLUSION

3

INTRODUCTION

• Introduction of TEOAEs

4

THE INDENPENDENT SUB-BAND FUNCTION MODEL

5

THE INDENPENDENT SUB-BAND FUNCTION MODEL (cont.)

3133

2132

1131

31

3113

2112

1121

21

3113

2112

1111

11

bcbcbcs

bcbcbcs

bcbcbcs

C-1=Wc

6

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 segmentsx(t)=As(t) x(t)=a1s1(t)+a2s2(t)

Formula A

7

A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE

• Implement steps

Procure sub-band functions

Transform xn into a multi-dimensional

Separate vector

Into a two-dimensional

vector and separate

Comparing

n=n+1

8

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

9

A SINGLE SENSOR MIXTURE SIGNAL SEPARATION TECHNIQUE

• Solving

N

n

Q

q

nnq

nq saZZCsf

1 1111111 ,)(where

Φ2can be obtained by the same form as that of Φ1

10

SEPARATION EXPERIMENT

Artifact

Independent sub-band functions

11

SEPARATION EXPERIMENT

To transform into a 4-dimensional vector

Similitude coefficient (SC) and similitude phase diagram (SPD)

12

SEPARATION EXPERIMENT

DNLR method

Author’s method

13

CONCLUSION

• Need only one signal

• Similar coefficient is near to 1