Subspace representation learning for sparse linear arrays to localize more sources than sensors: A deep learning methodology
Localizing more sources than sensors with a sparse linear array (SLA) has long relied on
minimizing a distance between two covariance matrices and recent algorithms often utilize …
minimizing a distance between two covariance matrices and recent algorithms often utilize …
Low complexity DOA estimation based on weighted noise component subtraction for smart-home application
H Guan, S Ding, W Dai, X Tan, Y Long, J Liang - Applied Acoustics, 2025 - Elsevier
In smart home applications, accurate direction of arrival (DOA) estimation of sound sources
is essential for beamforming and product interaction features. However, domestic …
is essential for beamforming and product interaction features. However, domestic …
Deep Learning with Estimation and Complexity Guarantees for Signal Processing
KL Chen - 2024 - search.proquest.com
UNIVERSITY OF CALIFORNIA SAN DIEGO Deep Learning with Estimation and Complexity
Guarantees for Signal Processing A dissertation Page 1 UNIVERSITY OF CALIFORNIA SAN …
Guarantees for Signal Processing A dissertation Page 1 UNIVERSITY OF CALIFORNIA SAN …
[PDF][PDF] Similar hierarchical representation of speech and other complex sounds in the brain and deep residual networks: An MEG study
Listeners recognize a vast number of complex sounds, but vocal sounds, speech and song,
are essential for communication. Recently, deep neural networks (DNNs) have achieved …
are essential for communication. Recently, deep neural networks (DNNs) have achieved …
[PDF][PDF] Empowering Speech Processing with Deep Neural Networks: Theory and Applications
AFC Filter - kjason.github.io
Empowering Speech Processing with Deep Neural Networks: Theory and Applications
Page 1 Empowering Speech Processing with Deep Neural Networks: Theory and …
Page 1 Empowering Speech Processing with Deep Neural Networks: Theory and …