Graph Signal Separation Based on Smoothness or Sparsity in the Frequency Domain
Author:
Affiliation:
1. Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
2. Center for Intelligent Systems (CIS), EPFL, Lausanne, Switzerland
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Information Systems,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6884276/10040263/10064133.pdf?arnumber=10064133
Reference29 articles.
1. Robust blind separation of smooth graph signals using minimization of graph regularized mutual information
2. Simultaneous Graph Learning and Blind Separation of Graph Signal Sources
3. Convex Optimization
4. Demixing and Blind Deconvolution of Graph-Diffused Sparse Signals
5. Blind Source Separation of Graph Signals
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2. A New Approach for Graph Signal Separation Based on Smoothness;IEEE Transactions on Signal Processing;2024
3. A signel-channel blind signal separation method based on signal type difference for time-frequency overlapped signal;2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom);2023-12-21
4. A Closed-Form Solution for Graph Signal Separation Based on Smoothness;IEEE Transactions on Signal and Information Processing over Networks;2023
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