English(EN) CNN Models for Microphone Array Covariance Matrix Upsampling and Acoustic Imaging

CNN模型通过上采样麦克风阵列数据增强声学成像

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-03 04:00

研究人员开发了新颖的CNN模型，通过上采样麦克风阵列数据来增强声学成像。这些模型旨在提高空间分辨率，而无需额外的硬件。通过估计协方差矩阵，这些网络可以将4麦克风阵列的输入转换为可与32麦克风阵列相媲美的表示，从而显著改善声图可视化效果。 AI

影响这些CNN模型有可能用更少的硬件实现更复杂的声学分析，可能对机器人和环境监测等领域产生影响。

排序理由该条目是arXiv预印本，详细介绍了用于音频处理的新型神经网络架构。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Marianthi Adamopoulou, Parthasaarathy Sudarsanam, David Diaz-Guerra, Meng Jiang, Archontis Politis, Seyed Jalaleddin Mousavirad, Tuomas Virtanen, Jan Lundgren · 2026-07-03 04:00

用于麦克风阵列协方差矩阵上采样和声学成像的CNN模型

arXiv:2607.01295v1 Announce Type: cross Abstract: Acoustic imaging visualization is a core methodology in acoustics, enabling spatial analysis of sound sources and acoustic scenes. However, limited sensor availability in practical systems motivate approaches that enhance spatial …