Literatura científica selecionada sobre o tema "Subspaces methods"
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Artigos de revistas sobre o assunto "Subspaces methods"
Eiermann, Michael, e Oliver G. Ernst. "Geometric aspects of the theory of Krylov subspace methods". Acta Numerica 10 (maio de 2001): 251–312. http://dx.doi.org/10.1017/s0962492901000046.
Texto completo da fonteFreund, Roland W. "Model reduction methods based on Krylov subspaces". Acta Numerica 12 (maio de 2003): 267–319. http://dx.doi.org/10.1017/s0962492902000120.
Texto completo da fonteSia, Florence, e Rayner Alfred. "Tree-based mining contrast subspace". International Journal of Advances in Intelligent Informatics 5, n.º 2 (23 de julho de 2019): 169. http://dx.doi.org/10.26555/ijain.v5i2.359.
Texto completo da fonteLENG, JINSONG, e ZHIHU HUANG. "OUTLIERS DETECTION WITH CORRELATED SUBSPACES FOR HIGH DIMENSIONAL DATASETS". International Journal of Wavelets, Multiresolution and Information Processing 09, n.º 02 (março de 2011): 227–36. http://dx.doi.org/10.1142/s0219691311004067.
Texto completo da fonteLaaksonen, Jorma, e Erkki Oja. "Learning Subspace Classifiers and Error-Corrective Feature Extraction". International Journal of Pattern Recognition and Artificial Intelligence 12, n.º 04 (junho de 1998): 423–36. http://dx.doi.org/10.1142/s0218001498000270.
Texto completo da fonteSeshadri, P., S. Yuchi, G. T. Parks e S. Shahpar. "Supporting multi-point fan design with dimension reduction". Aeronautical Journal 124, n.º 1279 (27 de julho de 2020): 1371–98. http://dx.doi.org/10.1017/aer.2020.50.
Texto completo da fonteNagi, Sajid, Dhruba Kumar Bhattacharyya e Jugal K. Kalita. "A Preview on Subspace Clustering of High Dimensional Data". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 6, n.º 3 (21 de maio de 2013): 441–48. http://dx.doi.org/10.24297/ijct.v6i3.4466.
Texto completo da fonteZhou, Jie, Chucheng Huang, Can Gao, Yangbo Wang, Xinrui Shen e Xu Wu. "Weighted Subspace Fuzzy Clustering with Adaptive Projection". International Journal of Intelligent Systems 2024 (31 de janeiro de 2024): 1–18. http://dx.doi.org/10.1155/2024/6696775.
Texto completo da fontePang, Guansong, Kai Ming Ting, David Albrecht e Huidong Jin. "ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets". Journal of Artificial Intelligence Research 57 (29 de dezembro de 2016): 593–620. http://dx.doi.org/10.1613/jair.5228.
Texto completo da fonteIl’in, V. P. "Projection Methods in Krylov Subspaces". Journal of Mathematical Sciences 240, n.º 6 (28 de junho de 2019): 772–82. http://dx.doi.org/10.1007/s10958-019-04395-7.
Texto completo da fonteTeses / dissertações sobre o assunto "Subspaces methods"
Shank, Stephen David. "Low-rank solution methods for large-scale linear matrix equations". Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/273331.
Texto completo da fontePh.D.
We consider low-rank solution methods for certain classes of large-scale linear matrix equations. Our aim is to adapt existing low-rank solution methods based on standard, extended and rational Krylov subspaces to solve equations which may viewed as extensions of the classical Lyapunov and Sylvester equations. The first class of matrix equations that we consider are constrained Sylvester equations, which essentially consist of Sylvester's equation along with a constraint on the solution matrix. These therefore constitute a system of matrix equations. The second are generalized Lyapunov equations, which are Lyapunov equations with additional terms. Such equations arise as computational bottlenecks in model order reduction.
Temple University--Theses
UGWU, UGOCHUKWU OBINNA. "Iterative tensor factorization based on Krylov subspace-type methods with applications to image processing". Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1633531487559183.
Texto completo da fonteHossain, Mohammad Sahadet. "Numerical Methods for Model Reduction of Time-Varying Descriptor Systems". Doctoral thesis, Universitätsbibliothek Chemnitz, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-74776.
Texto completo da fonteAhmed, Nisar. "Implicit restart schemes for Krylov subspace model reduction methods". Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340535.
Texto completo da fonteShatnawi, Heba Awad Addad. "Frequency estimation using subspace methods". Thesis, Wichita State University, 2009. http://hdl.handle.net/10057/2419.
Texto completo da fonteThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering
Ensor, Jonathan Edward. "Subspace methods for eigenstructure assignment". Thesis, University of York, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341821.
Texto completo da fonteMestrah, Ali. "Identification de modèles sous forme de représentation d'état pour les systèmes à sortie binaire". Electronic Thesis or Diss., Normandie, 2023. http://www.theses.fr/2023NORMC255.
Texto completo da fonteThis thesis focuses on parametric modeling of invariant linear systems from binary output measurements. This identification problem is addressed via the use ofsubspace methods. These methods allow the estimation of state-space models, an added benefit of these methods being the fact that their implementation doesnot require the prior knowledge of the order of the system. These methods are initially adapted to high resolution data processing, the objective of this thesis istherefore their adaptation to the identification using binary measurements. In this thesis we propose three subspace methods. Convergence properties of two ofthem are established. Monte Carlo simulation results are presented to show the good performance, but also limits, of these methods
Nguyen, Hieu. "Linear subspace methods in face recognition". Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/12330/.
Texto completo da fonteTao, Dacheng. "Discriminative linear and multilinear subspace methods". Thesis, Birkbeck (University of London), 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438996.
Texto completo da fonteYu, Xuebo. "Generalized Krylov subspace methods with applications". Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1401937618.
Texto completo da fonteLivros sobre o assunto "Subspaces methods"
Demmel, James Weldon. Three methods for refining estimates of invariant subspaces. New York: Courant Institute of Mathematical Sciences, New York University, 1985.
Encontre o texto completo da fonteWatkins, David S. The matrix eigenvalue problem: GR and Krylov subspace methods. Philadelphia: Society for Industrial and Applied Mathematics, 2007.
Encontre o texto completo da fonteMats, Viberg, e Stoica Petre 1949-, eds. Subspace methods. Amsterdam: Elsevier, 1996.
Encontre o texto completo da fonteKatayama, Tohru. Subspace methods for system identification. London: Springer, 2005.
Encontre o texto completo da fonteKatayama, Tohru. Subspace Methods for System Identification. London: Springer London, 2005. http://dx.doi.org/10.1007/1-84628-158-x.
Texto completo da fonteSaad, Y. Krylov subspace methods on supercomputers. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1988.
Encontre o texto completo da fonteSogabe, Tomohiro. Krylov Subspace Methods for Linear Systems. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8532-4.
Texto completo da fonteHeeger, David J. Subspace methods for recovering rigid motion. Toronto, Ont: University of Toronto, 1990.
Encontre o texto completo da fonteJepson, Allan D. Linear subspace methods for recovering translational direction. Toronto: University of Toronto, Dept. of Computer Science, 1992.
Encontre o texto completo da fonteF, Chan Tony, e Research Institute for Advanced Computer Science (U.S.), eds. Preserving symmetry in preconditioned Krylov subspace methods. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1996.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Subspaces methods"
Schechter, Martin. "Estimates on Subspaces". In Linking Methods in Critical Point Theory, 131–44. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1596-7_6.
Texto completo da fonteDowney, R. G., e Jeffrey B. Remmel. "Effectively and Noneffectively Nowhere Simple Subspaces". In Logical Methods, 314–51. Boston, MA: Birkhäuser Boston, 1993. http://dx.doi.org/10.1007/978-1-4612-0325-4_10.
Texto completo da fonteNenciu, G. "Almost Invariant Subspaces for Quantum Evolutions". In Multiscale Methods in Quantum Mechanics, 83–97. Boston, MA: Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-0-8176-8202-6_7.
Texto completo da fonteFischer, Bernd. "Orthogonal Polynomials and Krylov Subspaces". In Polynomial Based Iteration Methods for Symmetric Linear Systems, 132–36. Wiesbaden: Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-663-11108-5_4.
Texto completo da fonteFroelich, John, e Michael Marsalli. "Operator Semigroups, Invariant Sets and Invariant Subspaces". In Algebraic Methods in Operator Theory, 10–14. Boston, MA: Birkhäuser Boston, 1994. http://dx.doi.org/10.1007/978-1-4612-0255-4_2.
Texto completo da fonteIlin, Valery P. "Multi-preconditioned Domain Decomposition Methods in the Krylov Subspaces". In Lecture Notes in Computer Science, 95–106. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57099-0_9.
Texto completo da fonteAnton, Cristina, e Iain Smith. "Model Based Clustering of Functional Data with Mild Outliers". In Studies in Classification, Data Analysis, and Knowledge Organization, 11–19. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09034-9_2.
Texto completo da fonteBoot, Tom, e Didier Nibbering. "Subspace Methods". In Macroeconomic Forecasting in the Era of Big Data, 267–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31150-6_9.
Texto completo da fonteFukui, Kazuhiro. "Subspace Methods". In Computer Vision, 1–5. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-03243-2_708-1.
Texto completo da fonteFukui, Kazuhiro. "Subspace Methods". In Computer Vision, 777–81. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_708.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Subspaces methods"
Zhou, Lei, Xiao Bai, Dong Wang, Xianglong Liu, Jun Zhou e Edwin Hancock. "Latent Distribution Preserving Deep Subspace Clustering". In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/617.
Texto completo da fonteRenaud, J. E., e G. A. Gabriele. "Sequential Global Approximation in Non-Hierarchic System Decomposition and Optimization". In ASME 1991 Design Technical Conferences. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/detc1991-0086.
Texto completo da fonteYing, Shihui, Lipeng Cai, Changzhou He e Yaxin Peng. "Geometric Understanding for Unsupervised Subspace Learning". In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/579.
Texto completo da fonteTripathy, Rohit, e Ilias Bilionis. "Deep Active Subspaces: A Scalable Method for High-Dimensional Uncertainty Propagation". In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98099.
Texto completo da fonteArora, Akhil, Alberto Garcia-Duran e Robert West. "Low-Rank Subspaces for Unsupervised Entity Linking". In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.emnlp-main.634.
Texto completo da fonteXie, Zhihui, Handong Zhao, Tong Yu e Shuai Li. "Discovering Low-rank Subspaces for Language-agnostic Multilingual Representations". In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.emnlp-main.379.
Texto completo da fonteSmith, Malcolm J., T. S. Koko e I. R. Orisamolu. "Comparative Assessment of Optimal Control Methods With Integrated Performance Constraints". In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0947.
Texto completo da fonteBahamonde, Juan S., Matteo Pini e Piero Colonna. "ACTIVE SUBSPACES FOR THE PRELIMINARY FLUID DYNAMIC DESIGN OF UNCONVENTIONAL TURBOMACHINERY". In VII European Congress on Computational Methods in Applied Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2016. http://dx.doi.org/10.7712/100016.2433.7806.
Texto completo da fonteAl-Seraji, Najm Abdulzahra Makhrib, Abeer Jabbar Al-Rikabi e Emad Bakr Al-Zangana. "Represent the space PG(3, 8) by subspaces and sub-geometries". In INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING ICCMSE 2021. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0114859.
Texto completo da fonteChapron, Maxime, Christophe Blondeau, Michel Bergmann, Itham Salah el Din e Denis Sipp. "SCALABLE CLUSTERED ACTIVE SUBSPACES FOR KRIGING REGRESSION IN HIGH DIMENSION". In 15th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control. Athens: Institute of Structural Analysis and Antiseismic Research National Technical University of Athens, 2023. http://dx.doi.org/10.7712/140123.10192.18902.
Texto completo da fonteRelatórios de organizações sobre o assunto "Subspaces methods"
Harris, D. B. Characterizing source regions with signal subspace methods: Theory and computational methods. Office of Scientific and Technical Information (OSTI), dezembro de 1989. http://dx.doi.org/10.2172/5041042.
Texto completo da fonteWang, Qiqi. Active Subspace Methods for Data-Intensive Inverse Problems. Office of Scientific and Technical Information (OSTI), abril de 2017. http://dx.doi.org/10.2172/1353429.
Texto completo da fonteConstantine, Paul. Active Subspace Methods for Data-Intensive Inverse Problems. Office of Scientific and Technical Information (OSTI), setembro de 2019. http://dx.doi.org/10.2172/1566065.
Texto completo da fonteCarson, Erin, Nicholas Knight e James Demmel. Avoiding Communication in Two-Sided Krylov Subspace Methods. Fort Belvoir, VA: Defense Technical Information Center, agosto de 2011. http://dx.doi.org/10.21236/ada555879.
Texto completo da fonteMeza, Juan C., e W. W. Symes. Deflated Krylov Subspace Methods for Nearly Singular Linear Systems. Fort Belvoir, VA: Defense Technical Information Center, fevereiro de 1987. http://dx.doi.org/10.21236/ada455101.
Texto completo da fonteNeedell, Deanna, e Rachel Ward. Two-subspace Projection Method for Coherent Overdetermined Systems. Claremont Colleges Digital Library, 2012. http://dx.doi.org/10.5642/tspmcos.2012.01.
Texto completo da fonteBui-Thanh, Tan. Active Subspace Methods for Data-Intensive Inverse Problems (Final Report). Office of Scientific and Technical Information (OSTI), fevereiro de 2019. http://dx.doi.org/10.2172/1494035.
Texto completo da fonteLi, Zhilin, e Kazufumi Ito. Subspace Iteration and Immersed Interface Methods: Theory, Algorithm, and Applications. Fort Belvoir, VA: Defense Technical Information Center, agosto de 2010. http://dx.doi.org/10.21236/ada532686.
Texto completo da fonteElman, Howard C. Multigrid and Krylov Subspace Methods for the Discrete Stokes Equations. Fort Belvoir, VA: Defense Technical Information Center, junho de 1994. http://dx.doi.org/10.21236/ada598913.
Texto completo da fonteFreund, R. W., e N. M. Nachtigal. A new Krylov-subspace method for symmetric indefinite linear systems. Office of Scientific and Technical Information (OSTI), outubro de 1994. http://dx.doi.org/10.2172/10190810.
Texto completo da fonte