Results 41 to 50 of about 256,120 (256)
s-Goodness for Low-Rank Matrix Recovery
Abstract and Applied Analysis, 2013 Low-rank matrix recovery (LMR) is a rank minimization problem subject to linear equality constraints, and it arises in many fields such as signal and image processing, statistics, computer vision, and system identification and control.
Lingchen Kong +2 more
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Parameter Optimization for Low-Rank Matrix Recovery in Hyperspectral Imaging
Applied Sciences, 2023 An approach to parameter optimization for the low-rank matrix recovery method in hyperspectral imaging is discussed. We formulate an optimization problem with respect to the initial parameters of the low-rank matrix recovery method.
Monika Wolfmayr
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Toeplitz matrix completion via a low-rank approximation algorithm
Journal of Inequalities and Applications, 2020 In this paper, we propose a low-rank matrix approximation algorithm for solving the Toeplitz matrix completion (TMC) problem. The approximation matrix was obtained by the mean projection operator on the set of feasible Toeplitz matrices for every ...
Ruiping Wen, Yaru Fu
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Survey on Probabilistic Models of Low-Rank Matrix Factorizations
Entropy, 2017 Low-rank matrix factorizations such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD) and Non-negative Matrix Factorization (NMF) are a large class of methods for pursuing the low-rank approximation of a given data matrix.
Jiarong Shi, Xiuyun Zheng, Wei Yang
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A Geometric Approach to Low-Rank Matrix Completion [PDF]
IEEE Transactions on Information Theory, 2012 The low-rank matrix completion problem can be succinctly stated as follows: given a subset of the entries of a matrix, find a low-rank matrix consistent with the observations. While several low-complexity algorithms for matrix completion have been proposed so far, it remains an open problem to devise search procedures with provable performance ...
Wei Dai 0001 +2 more
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Robust low‐rank Hankel matrix recovery for skywave radar slow‐time samples
IET Radar, Sonar & Navigation, 2021 In skywave radar, the slow‐time samples received in a certain range‐azimuth cell are usually processed for signal analysis and target detection. Particularly, to extract the principal components, such as sea clutter and target signal, in slow‐time ...
Baiqiang Zhang, Junhao Xie, Wei Zhou
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Robust low-rank abundance matrix estimation for hyperspectral unmixing
The Journal of Engineering, 2019 Hyperspecral unmixing (HU) is one of the crucial steps of hyperspectral image (HSI) processing. The process of HU can be divided into end-member extraction and abundance estimation.
Fan Feng +4 more
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Thresholding Approach for Low-Rank Correlation Matrix Based on MM Algorithm
Entropy, 2022 Background: Low-rank approximation is used to interpret the features of a correlation matrix using visualization tools; however, a low-rank approximation may result in an estimation that is far from zero, even if the corresponding original value is zero.
Kensuke Tanioka +2 more
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Low-rank matrix approximation in the infinity norm [PDF]
Linear Algebra and its Applications, 2019 12 pages, 3 ...
Gillis, Nicolas, Shitov, Yaroslav
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A Deterministic Theory of Low Rank Matrix Completion [PDF]
IEEE Transactions on Information Theory, 2020 The problem of completing a large low rank matrix using a subset of revealed entries has received much attention in the last ten years. The main result of this paper gives a necessary and sufficient condition, stated in the language of graph limit theory, for a sequence of matrix completion problems with arbitrary missing patterns to be asymptotically ...
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