Results 21 to 30 of about 3,813,510 (369)
Frontiers in Neuroscience, 2022 Multi-modal magnetic resonance imaging (MRI) is widely used for diagnosing brain disease in clinical practice. However, the high-dimensionality of MRI images is challenging when training a convolution neural network.
Liangliang Liu +5 more
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Distributed Bayesian Matrix Decomposition for Big Data Mining and Clustering [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2020 Matrix decomposition is one of the fundamental tools to discover knowledge from big data generated by modern applications. However, it is still inefficient or infeasible to process very big data using such a method in a single machine. Moreover, big data
Chihao Zhang +3 more
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Incremental multi‐view correlated feature learning based on non‐negative matrix factorisation
IET Computer Vision, 2021 In real‐world applications, large amounts of data from multiple sources come in the form of streams. This makes multi‐view feature learning cost much time when new instances rise incrementally.
Liang Zhao +3 more
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On decomposition of k-tridiagonal ℓ-Toeplitz matrices and its applications
Special Matrices, 2015 We consider a k-tridiagonal ℓ-Toeplitz matrix as one of generalizations of a tridiagonal Toeplitz matrix. In the present paper, we provide a decomposition of the matrix under a certain condition.
Ohashi A., Sogabe T., Usuda T.S.
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IET Control Theory & Applications, 2023 The approximating sequence Riccati equation method is an efficient approach for solving the nonlinear optimal control problems, but its neglect of nonlinear dynamics and necessary optimality condition makes the control law difficult to satisfy the ...
Jianfeng Sun, Xuesong Chen
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Multiresolution matrix factorisation as a compression method for smart meter data
The Journal of Engineering, 2020 The development of a smart grid electricity distribution network with advanced technology in smart metering will produce a massive amount of data. However, the limitation in communication network bandwidth makes it hard to transmit these data to the ...
Arfah Ahmad +5 more
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Special Matrices, 2020 An important decomposition for unitary matrices, the CMV-decomposition, is extended to general non-unitary matrices. This relates to short recurrence relations constructing biorthogonal bases for a particular pair of extended Krylov subspaces.
Van Buggenhout Niel +2 more
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Orthogonal tucker decomposition using factor priors for 2D+3D facial expression recognition
IET Biometrics, 2021 In this article, an effective approach is proposed to recognise the 2D+3D facial expression automatically based on orthogonal Tucker decomposition using factor priors (OTDFPFER).
Yunfang Fu +4 more
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Constructive quantum scaling of unitary matrices [PDF]
, 2016 In this work we present a method of decomposition of arbitrary unitary matrix $U\in\mathbf U(2^k)$ into a product of single-qubit negator and controlled-$\sqrt{\mbox{NOT}}$ gates.
Glos, Adam, Sadowski, Przemysław
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Reliable data transmission in wireless sensor networks with data decomposition and ensemble recovery
Mathematical Biosciences and Engineering, 2019 Wireless sensor networks (WSNs) are usually used to helps many basic scientific works to gather and observe environmental data, whose completeness and accuracy are the key to ensuring the success of scientific works.
Fengyong Li, Gang Zhou, Jingsheng Lei
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