TY - GEN
T1 - Distributed Pressure Matching for Personal Sound Zone Control Using Diffusion Adaptation
AU - Zhang, Mengfei
AU - Zhang, Junqing
AU - Chen, Jie
AU - Richard, Cedric
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Personal sound zone (PSZ) systems, which aim to create listening (bright) and silent (dark) zones in neighboring regions of space, are often based on time-varying acoustics. Conventional adaptive-based methods for handling PSZ tasks suffer from the collection and processing of acoustic transfer functions (ATFs) between all the matching microphones and all the loudspeakers in a centralized manner, resulting in high calculation complexity and costly accuracy require-ments. This paper presents a distributed pressure-matching (PM) method relying on diffusion adaptation (DPM-D) to spread the com-putational load amongst nodes in order to overcome these issues. The global PM problem is defined as a sum of local costs, and the diffusion adaption approach is then used to create a distributed solution that just needs local information exchanges. Simulations over multi-frequency bins and a computational complexity analysis are conducted to evaluate the properties of the algorithm and to compare it with centralized counterparts.
AB - Personal sound zone (PSZ) systems, which aim to create listening (bright) and silent (dark) zones in neighboring regions of space, are often based on time-varying acoustics. Conventional adaptive-based methods for handling PSZ tasks suffer from the collection and processing of acoustic transfer functions (ATFs) between all the matching microphones and all the loudspeakers in a centralized manner, resulting in high calculation complexity and costly accuracy require-ments. This paper presents a distributed pressure-matching (PM) method relying on diffusion adaptation (DPM-D) to spread the com-putational load amongst nodes in order to overcome these issues. The global PM problem is defined as a sum of local costs, and the diffusion adaption approach is then used to create a distributed solution that just needs local information exchanges. Simulations over multi-frequency bins and a computational complexity analysis are conducted to evaluate the properties of the algorithm and to compare it with centralized counterparts.
KW - Personal sound zone
KW - diffusion adaptation
KW - distributed networks
KW - pressure matching
UR - https://www.scopus.com/pages/publications/85185004170
U2 - 10.1109/CAMSAP58249.2023.10403471
DO - 10.1109/CAMSAP58249.2023.10403471
M3 - 会议稿件
AN - SCOPUS:85185004170
T3 - 2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023
SP - 501
EP - 505
BT - 2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023
Y2 - 10 December 2023 through 13 December 2023
ER -