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采用球形麦克风阵列的压缩感知技术。

Compressive sensing with a spherical microphone array.

作者信息

Fernandez-Grande Efren, Xenaki Angeliki

机构信息

Acoustic Technology, Department of Electrical Engineering, Technical University of Denmark (DTU), Building 352, Ørsteds Plads, DK-2800 Kongens Lyngby, Denmark

出版信息

J Acoust Soc Am. 2016 Feb;139(2):EL45-9. doi: 10.1121/1.4942546.

DOI:10.1121/1.4942546
PMID:26936583
Abstract

A wave expansion method is proposed in this work, based on measurements with a spherical microphone array, and formulated in the framework provided by Compressive Sensing. The method promotes sparse solutions via ℓ1-norm minimization, so that the measured data are represented by few basis functions. This results in fine spatial resolution and accuracy. This publication covers the theoretical background of the method, including experimental results that illustrate some of the fundamental differences with the "conventional" least-squares approach. The proposed methodology is relevant for source localization, sound field reconstruction, and sound field analysis.

摘要

本文提出了一种基于球形传声器阵列测量的波扩展方法,该方法在压缩感知提供的框架下进行公式化。该方法通过ℓ1范数最小化来促进稀疏解,从而使测量数据由少数基函数表示。这导致了良好的空间分辨率和精度。本出版物涵盖了该方法的理论背景,包括实验结果,这些结果说明了与“传统”最小二乘法的一些基本差异。所提出的方法适用于声源定位、声场重建和声场分析。

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Compressive sensing with a spherical microphone array.采用球形麦克风阵列的压缩感知技术。
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引用本文的文献

1
A Sound Source Identification Algorithm Based on Bayesian Compressive Sensing and Equivalent Source Method.一种基于贝叶斯压缩感知和等效源法的声源识别算法
Sensors (Basel). 2020 Feb 6;20(3):865. doi: 10.3390/s20030865.
2
Estimation of surface impedance at oblique incidence based on sparse array processing.基于稀疏阵列处理的斜入射表面阻抗估计
J Acoust Soc Am. 2017 Jun;141(6):4115. doi: 10.1121/1.4983756.