Results 21 to 30 of about 107,644 (266)
Prediction of Remaining Useful Life of the Lithium-Ion Battery Based on Improved Particle Filtering
Remaining useful life (RUL) prediction of lithium-ion batteries plays an important role in battery failure prediction and health management (PHM).
Tiezhou Wu +3 more
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Singular Vectors From Singular Values
8 ...
Weiwei Xu, Michael K. Ng 0001
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Adaptive shrinkage of singular values [PDF]
To recover a low rank structure from a noisy matrix, truncated singular value decomposition has been extensively used and studied. Recent studies suggested that the signal can be better estimated by shrinking the singular values. We pursue this line of research and propose a new estimator offering a continuum of thresholding and shrinking functions. To
Josse, Julie, Sardy, Sylvain
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GPU accelerated singular value thresholding
Matrix completion (MC) is widely used in machine learning and signal processing to fill in the missing data of an incomplete observation matrix. Singular value thresholding (SVT) is one of the most popular algorithms among numerous MC methods.
Xiaotong Li, Karel Adámek, Wes Armour
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Singular Value Decomposition of Complexes [PDF]
Singular value decompositions of matrices are widely used in numerical linear algebra with many applications. In this paper, we extend the notion of singular value decompositions to finite complexes of real vector spaces. We provide two methods to compute them and present several applications.
Danielle A. Brake +4 more
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Privacy-Preserving Federated Singular Value Decomposition
Singular value decomposition (SVD) is a fundamental technique widely used in various applications, such as recommendation systems and principal component analyses.
Bowen Liu, Balázs Pejó, Qiang Tang
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5 pages, no figures; a few clarifying comments ...
Horowitz, Gary T., Myers, Robert
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Voltage-source rectifiers (VSRs) have been widely used in modern power grids. The inductive grid impedance of the power grid poses a serious threat to the stability of the VSR.
Kai Wang +3 more
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Singular Values for ReLU Layers [PDF]
Despite their prevalence in neural networks we still lack a thorough theoretical characterization of ReLU layers. This paper aims to further our understanding of ReLU layers by studying how the activation function ReLU interacts with the linear component of the layer and what role this interaction plays in the success of the neural network in achieving
Sören Dittmer +2 more
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Perturbation bounds for eigenvalues of diagonalizable matrices and singular values
Perturbation bounds for eigenvalues of diagonalizable matrices are derived. Perturbation bounds for singular values of arbitrary matrices are also given. We generalize some existing results.
Duanmei Zhou +3 more
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