Generalized Bilinear Factorization via Hybrid Vector Message Passing

Generalized bilinear factorization (GBF), in which two matrices are recovered from noisy and typically compressed measurements of their product, arises in various applications such as blind channel-and-signal estimation, image completion, and compressed video foreground and background separation. In...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 72; S. 5675 - 5690
Hauptverfasser:	Jiang, Hao, Yuan, Xiaojun, Guo, Qinghua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation algorithms Background noise Closed form solutions Convergence Correlation Covariance matrices Damping Exact solutions expectation propagation Factorization Free energy Generalized bilinear factorization Inference algorithms Inverse problems Message passing Signal processing algorithms Sparse matrices variational free energy minimization variational message passing Vectors Video compression
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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