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Updated: Dec 29, 2025

A Method to Study Adaptation to Left-Right Reversed Audition
Published on: October 29, 2018
Adaptive reweighting homotopy algorithm based compressive spherical beamforming with spherical microphone arrays
Shijia Yin1, Zhigang Chu1, Yongxiang Zhang1
1State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, People's Republic of China.
Abstract:
Compressive spherical beamforming (CSB) with spherical microphone arrays enjoys high spatial resolution and strong sidelobes suppression at medium to high frequencies. In this paper, the adaptive reweighting homotopy (ARH) algorithm is adapted to CSB, and the proposed method is abbreviated as ARH-CSB, which bypasses a priori signal-to-noise ratio (SNR) estimation. ARH-CSB iteratively solves the CSB model by determining the support set and adaptively searching for weights while estimating the source strength. Simulations and experiments demonstrate that ARH-CSB can effectively identify acoustic sources. Furthermore, compared to CSB solved by ℓ1-norm minimization algorithm and iterative reweighted ℓ1-norm minimization algorithm, ARH-CSB does not depend on a priori SNR and has better adaptability to low SNR, stronger robustness, higher weak sources quantification accuracy, and faster computation speed.
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