PETRELS: Parallel Subspace Estimation and Tracking by Recursive Least Squares From Partial Observations

Many real world datasets exhibit an embedding of low-dimensional structure in a high-dimensional manifold. Examples include images, videos and internet traffic data. It is of great significance to estimate and track the low-dimensional structure with small storage requirements and computational comp...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 61; H. 23; S. 5947 - 5959
Hauptverfasser:	Yuejie Chi, Eldar, Yonina C., Calderbank, Robert
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.12.2013 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Applied sciences Approximation algorithms Convergence Detection, estimation, filtering, equalization, prediction Estimation Exact sciences and technology Information, signal and communications theory Internet Least squares approximations Least squares method Matrix completion Networks Noise reduction online algorithms partial observations Recursive recursive least squares Signal and communications theory Signal processing algorithms Signal, noise Sparse matrices subspace identification and tracking Subspaces Telecommunications and information theory Tracking Vectors Parameter estimation Direction-of-arrival estimation State of the art partial observations Noise reduction Signal estimation Video signal recursive least squares Remote sensing Least squares method Matrix completion Target tracking subspace identification and tracking Subspace method Video technique Algorithm Computational complexity online algorithms Videocommunication Batch process On line processing Recursive method Signal processing Numerical simulation Internet Remote supervision
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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