Search Results - TENSOR ANALYSIS

Principal Tensor Embedding for Unsupervised Tensor Learning by Claudio Turchetti, Laura Falaschetti, Lorenzo Manoni

Subjects: “…multiway analysis…”
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Tensor Methods in Biomedical Image Analysis by Farnaz Sedighin

“…Considering this reality, in this paper, we aim to have a comprehensive review on tensor-based methods in biomedical image analysis. …”
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Accelerated Tensor Robust Principal Component Analysis via Factorized Tensor Norm Minimization by Geunseop Lee

“…In this paper, we aim to develop an efficient algorithm for the solving Tensor Robust Principal Component Analysis (TRPCA) problem, which focuses on obtaining a low-rank approximation of a tensor by separating sparse and impulse noise. …”
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Efficient Tensor Robust Principal Analysis via Right-Invertible Matrix-Based Tensor Products by Zhang Huang, Jun Feng, Wei Li

Subjects: “…tensor robust principal component analysis (TRPCA)…”
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Extension of Calculus Operations in Cartesian Tensor Analysis by Yiyu Lu, Peng Yue, Sibei Wei

Subjects: “…tensor analysis…”
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Tensor-Based Harmonic Analysis of Distribution Systems by Muhammad Ramzan, Ali Othman, Neville R. Watson

Subjects: “…tensors…”
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Simultaneous analysis and quality assurance for diffusion tensor imaging. by Carolyn B Lauzon, Andrew J Asman, Michael L Esparza, Scott S Burns, Qiuyun Fan, Yurui Gao, Adam W Anderson, Nicole Davis, Laurie E Cutting, Bennett A Landman

“…The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. …”
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Tensor‐structured decomposition improves systems serology analysis by Zhixin Cyrillus Tan, Madeleine C Murphy, Hakan S Alpay, Scott D Taylor, Aaron S Meyer

“…Here, we report that coupled matrix–tensor factorization (CMTF) can reduce these data into consistent patterns by recognizing the intrinsic structure of these data. …”
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A Color Image Watermarking Based on Tensor Analysis by Haiyong Xu, Gangyi Jiang, Mei Yu, Ting Luo

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Blind Spots Analysis of Magnetic Tensor Localization Method by Lei Xu, Xianyuan Huang, Zhonghua Dai, Fuli Yuan, Xu Wang, Jinyu Fan

“…In order to compare and analyze the positioning efficiency of the magnetic tensor location method, this paper studies the blind spots of the magnetic tensor location method. …”
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Tensor Analysis of Tropical Cyclone Boundary Layer Turbulence by Shanghong Wang, Xu Zhang

“…The horizontal components of diffusive tendencies contribute at magnitudes comparable to the vertical components. Alignment analysis using tensor decomposition demonstrates that strain‐rotation interactions dominate turbulent stress transporting in the boundary layer, highlighting limitations in the classical Boussinesq hypothesis. …”
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Classical and Quantum Algorithms for Tensor Principal Component Analysis by Matthew B. Hastings

“…We present classical and quantum algorithms based on spectral methods for a problem in tensor principal component analysis. The quantum algorithm achieves a $quartic$ speedup while using exponentially smaller space than the fastest classical spectral algorithm, and a super-polynomial speedup over classical algorithms that use only polynomial space. …”
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Tensor network analysis of the maple-leaf antiferromagnet spangolite by Philipp Schmoll, Harald O. Jeschke, Yasir Iqbal

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rTensor: An R Package for Multidimensional Array (Tensor) Unfolding, Multiplication, and Decomposition by James Li, Jacob Bien, Martin T. Wells

Subjects: “…tensor…”
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Tensor decomposition for painting analysis. Part 1: pigment characterization by Irina M. Ciortan, Tina G. Poulsson, Sony George, Jon Y. Hardeberg

“…In order to understand the photo-degradation mechanisms and their impact on fugitive materials, high-end scientific analysis is required. In a two-part article, we present a multi-modal approach to model fading effects in the spectral, temporal (first part) and spatial dimensions (second part). …”
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New analysis of ηπ tensor resonances measured at the COMPASS experiment by A. Jackura, C. Fernández-Ramírez, M. Mikhasenko, A. Pilloni, V. Mathieu, J. Nys, V. Pauk, A.P. Szczepaniak, G. Fox, M. Aghasyan, R. Akhunzyanov, M.G. Alexeev, G.D. Alexeev, A. Amoroso, V. Andrieux, N.V. Anfimov, V. Anosov, A. Antoshkin, K. Augsten, W. Augustyniak, A. Austregesilo, C.D.R. Azevedo, B. Badełek, F. Balestra, M. Ball, J. Barth, R. Beck, Y. Bedfer, J. Bernhard, K. Bicker, E.R. Bielert, R. Birsa, M. Bodlak, P. Bordalo, F. Bradamante, A. Bressan, M. Büchele, V.E. Burtsev, W.-C. Chang, C. Chatterjee, M. Chiosso, I. Choi, A.G. Chumakov, S.-U. Chung, A. Cicuttin, M.L. Crespo, S. Dalla Torre, S.S. Dasgupta, S. Dasgupta, O.Yu. Denisov, L. Dhara, S.V. Donskov, N. Doshita, Ch. Dreisbach, W. Dünnweber, R.R. Dusaev, M. Dziewiecki, A. Efremov, P.D. Eversheim, M. Faessler, A. Ferrero, M. Finger, M. Finger, jr., H. Fischer, C. Franco, N. du Fresne von Hohenesche, J.M. Friedrich, V. Frolov, E. Fuchey, F. Gautheron, O.P. Gavrichtchouk, S. Gerassimov, J. Giarra, F. Giordano, I. Gnesi, M. Gorzellik, A. Grasso, M. Grosse Perdekamp, B. Grube, T. Grussenmeyer, A. Guskov, D. Hahne, G. Hamar, D. von Harrach, F.H. Heinsius, R. Heitz, F. Herrmann, N. Horikawa, N. d'Hose, C.-Y. Hsieh, S. Huber, S. Ishimoto, A. Ivanov, Yu. Ivanshin, T. Iwata, V. Jary, R. Joosten, P. Jörg, E. Kabuß, A. Kerbizi, B. Ketzer, G.V. Khaustov, Yu.A. Khokhlov, Yu. Kisselev, F. Klein, J.H. Koivuniemi, V.N. Kolosov, K. Kondo, K. Königsmann, I. Konorov, V.F. Konstantinov, A.M. Kotzinian, O.M. Kouznetsov, Z. Kral, M. Krämer, P. Kremser, F. Krinner, Z.V. Kroumchtein, Y. Kulinich, F. Kunne, K. Kurek, R.P. Kurjata, I.I. Kuznetsov, A. Kveton, A.A. Lednev, E.A. Levchenko, M. Levillain, S. Levorato, Y.-S. Lian, J. Lichtenstadt, R. Longo, V.E. Lyubovitskij, A. Maggiora, A. Magnon, N. Makins, N. Makke, G.K. Mallot, S.A. Mamon, B. Marianski, A. Martin, J. Marzec, J. Matoušek, H. Matsuda, T. Matsuda, G.V. Meshcheryakov, M. Meyer, W. Meyer, Yu.V. Mikhailov, M. Mikhasenko, E. Mitrofanov, N. Mitrofanov, Y. Miyachi, A. Nagaytsev, F. Nerling, D. Neyret, J. Nový, W.-D. Nowak, G. Nukazuka, A.S. Nunes, A.G. Olshevsky, I. Orlov, M. Ostrick, D. Panzieri, B. Parsamyan, S. Paul, J.-C. Peng, F. Pereira, M. Pešek, M. Pešková, D.V. Peshekhonov, N. Pierre, S. Platchkov, J. Pochodzalla, V.A. Polyakov, J. Pretz, M. Quaresma, C. Quintans, S. Ramos, C. Regali, G. Reicherz, C. Riedl, N.S. Rogacheva, D.I. Ryabchikov, A. Rybnikov, A. Rychter, R. Salac, V.D. Samoylenko, A. Sandacz, C. Santos, S. Sarkar, I.A. Savin, T. Sawada, G. Sbrizzai, P. Schiavon, T. Schlüter, K. Schmidt, H. Schmieden, K. Schönning, E. Seder, A. Selyunin, L. Silva, L. Sinha, S. Sirtl, M. Slunecka, J. Smolik, A. Srnka, D. Steffen, M. Stolarski, O. Subrt, M. Sulc, H. Suzuki, A. Szabelski, T. Szameitat, P. Sznajder, M. Tasevsky, S. Tessaro, F. Tessarotto, A. Thiel, J. Tomsa, F. Tosello, V. Tskhay, S. Uhl, B.I. Vasilishin, A. Vauth, J. Veloso, A. Vidon, M. Virius, S. Wallner, T. Weisrock, M. Wilfert, J. ter Wolbeek, K. Zaremba, P. Zavada, M. Zavertyaev, E. Zemlyanichkina, N. Zhuravlev, M. Ziembicki

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Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis by Cyril Atkinson-Clement, Serge Pinto, Alexandre Eusebio, Olivier Coulon

“…In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. …”
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Underdetermined mixing matrix estimation algorithm based on tensor analysis by Baoze MA, Guojun LI, Cuiling XIANG, Yang XU

“…Aiming at the problems of difficult to extract effective feature information and the slow convergence speed of the underdetermined matrix estimation, an underdetermined matrix estimation algorithm of instantaneous mixtures based on tensor analysis was proposed to overcome the constraint of signal sparsity.In the proposed algorithm, the symmetric third-order tensor was constructed via the autocovariance matrix of segmentation sub-block, which was compressed into a kernel tensor to reduce the size of the data.An enhanced line search technology was applied to speed up the convergence of alternating least squares method, and the factor matrix was used as the measure of the mixing matrix estimation, but the selection of the number of segmentation sub-blocks was an open problem.Experimental results demonstrate that the proposed algorithm outperforms the sparse transformation method and the traditional high-order statistical method in handling the underdetermined mixing matrix estimation.…”
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Performance analysis of the TensorFlow library with different optimisation algorithms by Maciej Wadas, Jakub Smołka

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Hybrid moment tensor inversion and numerical analysis of rock fracture by Zhang Lingfan, Chen Zhonghui, Qin Fan, Nian Gengqian, Chen Hongjie

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