Learning of robust spectral graph dictionaries for distributed processing

Learning of robust spectral graph dictionaries for distributed processing

Abstract We consider the problem of distributed representation of signals in sensor networks, where sensors exchange quantized information with their neighbors. The signals of interest are assumed to have a sparse representation with spectral graph dictionaries. We further model the spectral diction...

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Bibliographic Details
Main Authors: Dorina Thanou, Pascal Frossard
Format: Article
Language:English
Published: SpringerOpen 2018-10-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Distributed processing
Graph signal processing
Quantization
Polynomial dictionaries
Sparse approximation
Online Access:http://link.springer.com/article/10.1186/s13634-018-0584-2

Internet

http://link.springer.com/article/10.1186/s13634-018-0584-2

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