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A hybrid descent method with genetic algorithm for microphone array placement design

delete2013-03-01
delete46
PRE
AI
李
李志保 (Zhibao Li)
K
Ka Fai Cedric Yiu *
Z
Zhiguo Feng
DOI:10.1016/j.asoc.2012.02.027delete
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摘要

摘要

En 中文
In beamformer design, the microphone locations are often fixed and only the filter coefficients are varied in order to improve on the noise reduction performance. However, the positions of the microphone elements play an important role in the overall performance and should be optimized at the same time. However, this nonlinear optimization problem is non-convex and local search techniques might not yield the best result. This problem is addressed in this paper. A hybrid descent method is proposed which consists of a genetic algorithm together with a gradient-based method. The gradient-based method can help to locate the optimal solution rapidly around the start point, while the genetic algorithm is used to jump out from local minima. This hybrid method has the descent property and can help us to find the optimal placement for better beamformer design. Numerical examples are provided to demonstrate the effectiveness of the method. (C) 2012 Elsevier B. V. All rights reserved.
Keyword:
Beamformer design
Microphone array
Microphone placement
Genetic algorithm
Hybrid descent method
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期刊

Applied Soft Computing 封面图
Applied Soft Computing
IF:
6.6
论文数:
1.4W
被引数:
4.8W

机构

H
hong kong polytechnic university
学者数:
3.0W
论文数: 4.1W
被引数: 921
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