Acoustic Beamforming with Maximum SNR Criterion and Efficient Generalized Eigenvector Tracking

  • Toshihisa Tanaka
  • Mitsuaki Shiono
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8879)


A recently proposed adaptive acoustic beamformer based on the maximization of the output SNR (Max-SNR beamformer) has an advantage of requiring no information of transfer functions. A key technology to implement Max-SNR beamformers is to estimate generalized eigenvector (GEV) of covariance matrices of target signal and noise, which are basically unknown. We develop a novel GEV tracking algorithm with decaying time windows that enable Max-SNR beamformer to adapt rapidly moving sources. Simulation results support the analysis.


Direction Cosine Microphone Array Generalize Eigenvector Microphone Signal Gradient Ascent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Toshihisa Tanaka
    • 1
  • Mitsuaki Shiono
    • 1
  1. 1.Tokyo University of Agriculture and TechnologyKoganei-shiJapan

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