Brain source localization: A new method based on MUltiple SIgnal Classification algorithm and spatial sparsity of the field signal for electroencephalogram measurements

2013 ◽  
Vol 84 (8) ◽  
pp. 085117 ◽  
Author(s):  
P. Vergallo ◽  
A. Lay-Ekuakille
2013 ◽  
Vol 748 ◽  
pp. 634-639 ◽  
Author(s):  
Jian Rong Wang ◽  
Ju Zhang ◽  
Song Gun Hyon ◽  
Jian Guo Wei

In order to locate the sound source based on the microphone uniform linear array and reduce the impact of noise and reflection, improved multiple signal classification algorithm and a kind of weighted average filters be used in this paper. According to the microphone array speech processing characteristics, we improved the traditional multiple signal classification algorithm and designed a kind of weighted average filters. Then, we made the computer simulation experiments. The experimental results show that the location of the sound source is the peak with the highest power in the spatial spectrum. Besides, the frequency domain diagram is more smoothly and the power of the noise and reflection is effectively reduced except sound source through the weighted average processing. Therefore, improved multiple signal classification algorithm can achieve sound source localization based on the microphone uniform linear array. And the impact of the noise and reflection is effectively reduced by processing of the weighted average filters.


2006 ◽  
Vol 60 (6) ◽  
pp. 645-651 ◽  
Author(s):  
TETSUO UOHASHI ◽  
YOSHIHIRO KITAMURA ◽  
SUGURU ISHIZU ◽  
MOTOI OKAMOTO ◽  
NORIHITO YAMADA ◽  
...  

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