@inproceedings{69f10372fd244f68b5354dc5a8ec2932,
title = "Sound Zone Control Based on a Kronecker Second-Order Tensor Decomposition",
abstract = "In this work, we address the computational challenges in personal audio systems implemented within a room environment, which typically operate under a multi-input multi-output (MIMO) framework. Traditional control algorithms require long control filters to prevent performance degradation, substantially increasing the computational load due to matrix inversion and overall system complexity. We introduce a novel approach utilizing second-order Kronecker product decomposition, where the loudspeaker control filter is expressed as the Kronecker product of two shorter sub-filters. This method effectively reduces the matrix dimensions required for a single filter, significantly lowering computational complexity compared to traditional time-domain techniques. An iterative filter design is then employed to closely approximate the globally optimal solution. Simulation results demonstrate that our method achieves performance comparable to that of the conventional algorithm while significantly reducing computational demands.",
keywords = "Nearest Kronecker product, Personal sound zone, Pressure matching, Tensor Decomposition",
author = "Zhien Mao and Wen Zhang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 19th National Conference on Man-Machine Speech Communication, NCMMSC 2024 ; Conference date: 15-08-2024 Through 18-08-2024",
year = "2025",
doi = "10.1007/978-981-96-1045-7_13",
language = "英语",
isbn = "9789819610440",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "153--167",
editor = "Zhenhua Ling and Xie Chen and Askar Hamdulla and Liang He and Ya Li",
booktitle = "Man-Machine Speech Communication - 19th National Conference, NCMMSC 2024, Proceedings",
}