Neural Full-Rank Spatial Covariance Analysis for Blind Source Separation-Reference-Cited by-同舟云学术

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Neural Full-Rank Spatial Covariance Analysis for Blind Source Separation

Published:2021 Issue: Volume:28 Page:1670-1674
ISSN:1070-9908
Container-title:IEEE Signal Processing Letters
language:
Short-container-title:IEEE Signal Process. Lett.

Author:

Bando Yoshiaki^ORCID,Sekiguchi Kouhei^ORCID,Masuyama Yoshiki^ORCID,Nugraha Aditya Arie^ORCID,Fontaine Mathieu^ORCID,Yoshii Kazuyoshi^ORCID

Funder

JST ACT-X

JSPS KAKENHI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/97/9325893/09506855.pdf?arnumber=9506855

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Room impulse response reshaping-based expectation–maximization in an underdetermined reverberant environment;Computer Speech & Language;2024-11

2. Blind Source Separation of Electromagnetic Signals Based on Swish-Tasnet;Circuits, Systems, and Signal Processing;2024-07-16

3. Sound Source Separation Using Latent Variational Block-Wise Disentanglement;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

4. Determined BSS by Combination of IVA and DNN via Proximal Average;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

5. Efficient FPGA implementation for sound source separation using direction-informed multichannel non-negative matrix factorization;The Journal of Supercomputing;2024-03-06

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