Evaluation of vehicle interior sound quality using a continuous restricted Boltzmann machine-based DBN
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- 作者：Hai B. Huanga ; b ; huanghaibo214@my.swjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Ren X. Lia ; rxli@home.swjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Ming L. Yanga ; yml@home.swjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Teik C. Limb ; limt@ucmail.uc.edu" class="auth_mail" title="E-mail the corresponding author ; Wei P. Dinga ; dwp@home.swjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Sound quality evaluation ; Vehicle interior noise ; Feature extraction ; Continuous restricted Boltzmann machines ; Deep belief networks
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2017
- 出版时间：1 February 2017
- 年：2017
- 卷：84
- 期：part_PA
- 页码：245-267
- 全文大小：2961 K
文摘
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A new fusion acoustic feature set has been developed through comparison.
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An intelligent approach, CRBM-DBN, is proposed.
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CRBM-DBN outperforms three conventional methods in accuracy and stability.