Work

Adaptive optimization of the trade-off parameter in acoustic-contrast-control-pressure-matching for personal audio zones using genetic algorithms

Year: 2026

Type: article

Abstract: This paper is dedicated to solving the intrinsic problems of the traditional acoustic-contrast-control-pressure-matching (ACC-PM) algorithm that is commonly applied to realize the so-called personal audio zone (PAZ) concept. This is achieved by optimizing the trade-off parameter in the ACC-PM algorithm using the genetic algorithm (GA). Upon optimization, the trade-off parameter is no longer constant but becomes frequency- and circumstance-dependent. In-situ measurements demonstrate that the optimization can, in general, improve the sound compartmentalization performance of the PAZ system and, more importantly, enhance the numerical stability of the ACC-PM algorithm, making it more robust for practical application. An effective way to implement the optimization in practice is recommended at the end of the paper.

Source: Scientific Reports

DOI: 10.1038/s41598-026-42944-8

Authors: Yugang Zhu, Zhe Zhang, Yingqi Yin, Minghui Yang

Institutions: Tianjin University of Technology and Education, China Automotive Technology and Research Center, Southwest Jiaotong University

Language: English

Topic: Advanced Adaptive Filtering Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,690

Funder: Tianjin Municipal Science and Technology Bureau