Optimization of neural-network-based superdirective microphone-array system using a genetic algorithm

• Iseki Akihiro

  Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi

• Kinoshita Yuichiro

  Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi

• Ozawa Kenji

  Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi

抄録

A previous study indicated that superdirectivity is achieved with a microphone-array system consisting of seven microphones and a neural network. In this work, we aim to improve the directivity by optimizing the parameters of the neural network using a genetic algorithm. A computational simulation shows that the optimized system can produce superdirectivity with a half-width of five degrees. The optimized system improves the directivity because its side-lobes are suppressed by more than 10 dB compared with the results of the previous study. This suppression is also observed in terms of harmonic distortions. Moreover, in an examination using AM and FM waves as input signals, the optimized system achieves higher performances than those in the previous study.

収録刊行物

• Acoustical Science and Technology

  Acoustical Science and Technology 36 (4), 326-332, 2015

  一般社団法人 日本音響学会

キーワード

• Microphone array
• Neural network
• Genetic algorithm
• Superdirectivity

詳細情報

• CRID: 1390001205089441152
• NII論文ID: 130005086491
• NII書誌ID: AA11501808
• DOI: 10.1250/ast.36.326
• ISSN: 13475177
• ISSN: 03694232
• ISSN: 13463969
• NDL書誌ID: 026556436
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I026556436
• 本文言語コード: en
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