A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 6 Issue 1
Jan.  2019

IEEE/CAA Journal of Automatica Sinica

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    CiteScore: 11.2, Top 5% (Q1)
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Article Contents
Lichuan Liu, Karunakar Reddy Pottim and Sen M. Kuo, "Ear Field Adaptive Noise Control for Snoring: An Real-time Experimental Approach," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 158-166, Jan. 2019. doi: 10.1109/JAS.2019.1911339
Citation: Lichuan Liu, Karunakar Reddy Pottim and Sen M. Kuo, "Ear Field Adaptive Noise Control for Snoring: An Real-time Experimental Approach," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 158-166, Jan. 2019. doi: 10.1109/JAS.2019.1911339

Ear Field Adaptive Noise Control for Snoring: An Real-time Experimental Approach

doi: 10.1109/JAS.2019.1911339
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  • In this paper, an active noise control (ANC) system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer's bed partner. An adaptive least mean square (LMS) algorithm optimized for different kinds of snore signals is introduced and theoretically analyzed. Also, a residual noise masking approach is proposed to further reduce the effect of the snore noise without interfering with the LMS algorithm. Computer simulations followed by real-time experiments are conducted to demonstrate the feasibility of the snore ANC systems based on a pillow setup. For the optimum effect based on the characteristics of human hearing, the performance of the proposed approach is evaluated by using the multi-channel feedforward ANC systems based on the filtered-X least mean square (FXLMS) algorithm. Compared with a traditional headboard setup for snoring noise control, the proposed snore ANC systems optimized for ear field operation yield much higher noise reduction around the ears of the snorer's bed partner.


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