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On the Sparse Beamformer Design.

Mingjie Gao1, Ka Fai Cedric Yiu2, Sven Nordholm3

  • 1School of Mathematical Sciences, South China Normal University, Guangzhou 510000 , China. mjgao@m.scnu.edu.cn.

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Summary
This summary is machine-generated.

This study introduces a novel optimization method for acoustic beamformers, reducing computational complexity by simultaneously thinning filters and pruning arrays. The proposed sparse designs significantly decrease computational load with minimal performance impact.

Keywords:
array pruningbeamformer designsignal enhancementsparse filters

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Area of Science:

  • Acoustic signal processing
  • Array signal processing
  • Optimization techniques

Background:

  • Acoustic broadband beamformer design complexity increases with microphone count and filter length.
  • High filter coefficients lead to significant computational load.
  • Large array sizes also contribute to system complexity.

Purpose of the Study:

  • To address the computational complexity in acoustic broadband beamformer design.
  • To develop methods for reducing filter length and array size.
  • To achieve sparse designs for efficient implementation.

Main Methods:

  • A two-stage optimization model is proposed.
  • Simultaneous array pruning and filter thinning are employed.
  • The optimization model yields sparse beamformer designs.

Main Results:

  • Significant reduction in beamformer complexity is achieved.
  • The proposed method results in sparse filter coefficients (filter thinning).
  • Array size reduction (array pruning) is also realized.

Conclusions:

  • The developed optimization approach effectively reduces computational complexity.
  • Sparse beamformer designs maintain performance with reduced resource requirements.
  • The two-stage optimization model offers a viable solution for efficient beamformer implementation.