End-to-End Deep Learning-Based Adaptation Control for Linear Acoustic Echo Cancellation
Author:
Affiliation:
1. Chair of Multimedia Communications and Signal Processing (LMS), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics
Link
http://xplorestaging.ieee.org/ielx7/6570655/10304349/10288049.pdf?arnumber=10288049
Reference51 articles.
1. A Nonparametric VSS NLMS Algorithm
2. State-space architecture of the partitioned-block-based acoustic echo controller
3. Batch-Online Semi-Blind Source Separation Applied to Multi-Channel Acoustic Echo Cancellation
4. On Adjusting the Learning Rate in Frequency Domain Echo Cancellation With Double-Talk
5. Frequency-domain adaptive Kalman filter for acoustic echo control in hands-free telephones
Cited by 2 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. Design and Implementation of Adaptive Anti-jamming Line Frequency Communication Filter Based on RLS Algorithm;2024 4th International Conference on Electronics, Circuits and Information Engineering (ECIE);2024-05-24
2. Erratum to “End-to-End Deep Learning-Based Adaptation Control for Linear Acoustic Echo Cancellation”;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024
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