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Generalised Brans-Dicke cosmologyHolden, Damien James January 2002 (has links)
No description available.
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Analysis of numerical methods for some tensor equationsLiu, Dong Dong January 2018 (has links)
University of Macau / Faculty of Science and Technology. / Department of Mathematics
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A study of induced operators on symmetry classes of tensors /Tam, Tin-yau. January 1986 (has links)
Thesis--Ph. D., University of Hong Kong, 1986.
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A study of induced operators on symmetry classes of tensors譚天佑, Tam, Tin-yau. January 1986 (has links)
published_or_final_version / Mathematics / Doctoral / Doctor of Philosophy
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An all-at-once approach to nonnegative tensor factorizationsFlores Garrido, Marisol 11 1900 (has links)
Tensors can be viewed as multilinear arrays or generalizations of the notion of matrices. Tensor decompositions have applications in various fields such as psychometrics, signal processing, numerical linear algebra and data mining. When the data are nonnegative, the nonnegative tensor factorization (NTF) better reflects the underlying structure. With NTF it is possible to extract information from a given dataset and construct lower-dimensional bases that capture the main features of the set and concisely describe the original data.
Nonnegative tensor factorizations are commonly computed as the solution of a nonlinear bound-constrained optimization problem. Some inherent difficulties must be taken into consideration in order to achieve good solutions. Many existing methods for computing NTF optimize over each of the factors separately; the resulting algorithms are often slow to converge and difficult to control. We propose an all-at-once approach to computing NTF. Our method optimizes over all factors simultaneously and combines two regularization strategies to ensure that the factors in the decomposition remain bounded and equilibrated in norm.
We present numerical experiments that illustrate the effectiveness of our approach. We also give an example of digital-inpainting, where our algorithm is employed to construct a basis that can be used to restore digital images.
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Space group polynomial tensorsPhaneuf, Dan. January 1984 (has links)
No description available.
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Homogeneous polynomial tensors for double point groupsDesmier, Paul Edmond. January 1978 (has links)
No description available.
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An all-at-once approach to nonnegative tensor factorizationsFlores Garrido, Marisol 11 1900 (has links)
Tensors can be viewed as multilinear arrays or generalizations of the notion of matrices. Tensor decompositions have applications in various fields such as psychometrics, signal processing, numerical linear algebra and data mining. When the data are nonnegative, the nonnegative tensor factorization (NTF) better reflects the underlying structure. With NTF it is possible to extract information from a given dataset and construct lower-dimensional bases that capture the main features of the set and concisely describe the original data.
Nonnegative tensor factorizations are commonly computed as the solution of a nonlinear bound-constrained optimization problem. Some inherent difficulties must be taken into consideration in order to achieve good solutions. Many existing methods for computing NTF optimize over each of the factors separately; the resulting algorithms are often slow to converge and difficult to control. We propose an all-at-once approach to computing NTF. Our method optimizes over all factors simultaneously and combines two regularization strategies to ensure that the factors in the decomposition remain bounded and equilibrated in norm.
We present numerical experiments that illustrate the effectiveness of our approach. We also give an example of digital-inpainting, where our algorithm is employed to construct a basis that can be used to restore digital images.
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Investigation of left ventricular heart structure and functions using magnetic resonance diffusion tensor imagingWu, Yin, January 2008 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2008. / Includes bibliographical references. Also available in print.
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Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Medical Physics in the University of Canterbury /Chappell, Michael H. January 2007 (has links)
Thesis (Ph. D.)--University of Canterbury, 2007. / Typescript (photocopy). Includes bibliographical references (leaves 153-172). Also available via the World Wide Web.
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