Title :
A learning algorithm for adaptive microphone arrays based on mathematical programming methods
Author :
Suyama, Kenji ; Yashi, Ryuichi Hiraba
Author_Institution :
Sci. Univ. of Tokyo, Japan
Abstract :
This paper proposes a new learning algorithm for adaptive microphone arrays consisting of multi-channel adaptive linear filters. The algorithm is based on the interior point method, which is a very powerful mathematical programming method. In this algorithm, the learning problem of multi-channel adaptive linear filters is formulated as a quadratic programming (QP) problem with some constraints. The optimal filter coefficients are updated using the analytic center for a feasible region of this QP, and the feasible region is shrunk by a factor dependent on the error energy of learning. Using this strategy, a numerical stability of learning can be ensured. It is shown experimentally that this numerical stability can be always maintained, and that a high quality of target extraction can be achieved
Keywords :
acoustic arrays; acoustic signal processing; adaptive filters; mathematical programming; microphones; numerical stability; adaptive microphone arrays; interior point method; learning algorithm; learning error energy; learning numerical stability; learning problem; mathematical programming methods; multi-channel adaptive linear filters; optimal filter coefficients; quadratic programming; target extraction; Adaptive arrays; Adaptive filters; Convergence; Mathematical programming; Microphone arrays; Nonlinear filters; Numerical stability; Resonance light scattering; Signal processing; Signal processing algorithms;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
0-7803-6293-4
DOI :
10.1109/ICASSP.2000.859096