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Incremental algorithms for truncated higher-order singular value decompositions
BIT Numerical MathematicszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chao Zeng +2 more
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Truncated singular value decomposition for semantic-based data retrieval
2013 Third International Conference on Communications and Information Technology (ICCIT), 2013This paper addresses the increasingly encountered challenge of knowledge indexation. In the past decade, research on numerical schemes on knowledge indexation has been quite intensive. Vector space model is only based on the information contained in term weighting and does therefore not process the semantic contained in the sequence in which the words ...
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ECG signal compression using data extraction and truncated singular value decomposition
2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 2017In this paper a novel algorithm is used for compressing ECG data. The algorithm uses two techniques simultaneously to get a better compression of ECG data. Firstly Data extraction: a sampling technique based on a user defined threshold value is applied on ECG followed by Truncated Singular Value Decomposition.
Syed Salman Kabir +2 more
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A Trust-Region Method for Solving Truncated Complex Singular Value Decomposition
Journal of Computational MathematicsThe truncated singular value decomposition has been widely used in many areas of science including engineering, and statistics, etc. In this paper, the original truncated complex singular value decomposition problem is formulated as a Riemannian optimization problem on a product of two complex Stiefel manifolds, a practical algorithm based on the ...
Li, Jiaofen +4 more
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Neutron Spectrum Unfolding Using a Modified Truncated Singular Value Decomposition Method
Nuclear Science and Engineering, 1999A modified truncated singular value decomposition (MTSVD) is employed to unfold proton recoil pulse-height spectra into neutron energy spectra, using experimentally measured response functions. To illustrate the method, spectra from [sup 252]Cf and [sup 239]PuBe sources are unfolded.
D. Stuenkel +2 more
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Singular value decomposition for the truncated Hilbert transform: part II
Inverse Problems, 2011Hilbert transform is a very important tool in computed tomography. Image reconstruction from truncated tomographic data can be reduced to the problem of inverting the Hilbert transform knowing ψ on the interval [a2, a3], where a1 < a2 < a3 < a4. In this paper, we obtain a singular value decomposition for the operator .
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IEEE Transactions on Cybernetics, 2019
The problem of recovering missing data of an incomplete tensor has drawn more and more attentions in the fields of pattern recognition, machine learning, data mining, computer vision, and signal processing. Researches on this problem usually share a common assumption that the original tensor is of low-rank.
Zisen Fang +3 more
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The problem of recovering missing data of an incomplete tensor has drawn more and more attentions in the fields of pattern recognition, machine learning, data mining, computer vision, and signal processing. Researches on this problem usually share a common assumption that the original tensor is of low-rank.
Zisen Fang +3 more
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Velocity analysis by truncated singular value decomposition
SEG Technical Program Expanded Abstracts 1993, 1993Spagnolini, Umberto +2 more
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Aeromagnetic Compensation Using an Improved Truncated Singular Value Decomposition Method
2023 6th International Conference on Information Communication and Signal Processing (ICICSP), 2023Wenhua Song +3 more
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Quaternion higher-order singular value decomposition and its applications in color image processing
Information Fusion, 2023Kit Ian Kou
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