Blind source separation algorithm for convolution mixed signals

Blind source separation algorithm for convolution mixed signals

Chunli Wang Quanyu Wang  Yuping Cao 

College of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

Corresponding Author Email: 
wcl@mail.lzjtu.cn
Page: 
103-107
|
DOI: 
10.18280/rces.040401
Received: 
|
Accepted: 
|
Published: 
31 December 2017
| Citation

OPEN ACCESS

Abstract: 

In the actual speech enhancement application, a large number of observation data need longer filters. The time domain algorithm has the disadvantages of large computation amount and slow processing speed. Transforming the time domain convolution operation into the frequency domain product operation can not only avoid the complicated convolution operation, but also reduce the calculation amount to a large extent, and improve the effectiveness of the blind source separation algorithm. Simulation experiment results show that the blind deconvolution algorithm in the frequency domain can improve the intelligibility and articulation of separated speech.

Keywords: 

Speech Enhancement, Frequency Domain, Convolution, Blind Source Separation, Effectiveness

1. Introduction
2. Mathematical Model of Convolution Mixing
3. Frequency Domain Blind Deconvolution Algorithm
4. Simulation Experiment and Analysis of Results
5. Conclusions
Acknowledgement
  References

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