Results 181 to 190 of about 13,343 (226)

Singular-Value Decomposition (SVD)

2011
In the previous section, we utilized the orthogonal direct-sum decomposi- tions $$ E^n = V_1 \oplus W_{1\,\,} \,$$ and $$ E^m = V_2 \oplus W_2 $$ where\( V_1 = Sp(A),W_1 = {V_1}^ \bot,W_2 = Ker(A),\)and\( V_2 = {W_2}^{\bot,}\)to define the Moore-Penrose inverseA- of the n by m matrix A in \( y = Ax \) a linear transformation from \( E^m \,\)
Jack Dongarra, Piotr Luszczek, Felix Wolf, Jesper Larsson Träff, Patrice Quinton, Hermann Hellwagner, Martin Fränzle, Christian Lengauer, Luis H Ceze, Kei Hiraki, Rolf Riesen, Arthur B. Maccabe, John Feo, Kamesh Madduri, Tanguy Risset, Maleq Khan, V. S. Anil Kumar, Madha V. Marathe, Paula E. Stretz, Sandhya Dwarkadas, Laxmikant V. Kalé, Edgar Solomonik, Michael Bader, Hans-Joachim Bungartz, Miriam Mehl, Thomas Huckle, Matous Sedlacek, David A Bader, Guojing Cong, Anshul Gupta, Matthias Müller, Brian Whitney, Robert Henschel, Kalyan Kumaran, Josep Torrellas, Lawrence Rauchwerger, Eric Polizzi, Markus Püschel, Franz Franchetti, Yevgen Voronenko, Frederica Darema, Ryan Newton, Amol Ghoting, Konstantin Makarychev, Xiaoye Sherry Li, James Demmel, John Gilbert, Laura Grigori, Meiyue Shao, Wen mei Hwu, David A. Bader, Guojing Cong, José Flich, Sudhakar Yalamanchili, Michael L. Scott, Jaroslaw Zola, Srinivas Aluru, Srinivas Aluru, James R. Reinders   +58 more
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Analysis of scintigrams by singular value decomposition (SVD) technique

Annals of Nuclear Medicine, 1994
The singular value decomposition (SVD) method is presented as a potential tool for analyzing gamma camera images. Mathematically image analysis is a study of matrixes as the standard scintigram is a digitized matrix presentation of the recorded photon fluence from radioactivity of the object.
S E, Savolainen, B K, Liewendahl
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Evaluation of Singular Value Decomposition (SVD) Enhanced Upscaling in Reservoir Simulation

Volume 11: Petroleum Technology, 2020
Abstract Reservoir upscaling is an important step in reservoir modeling for converting highly detailed geological models to simulation grids. It substitutes a heterogeneous model that consists of high-resolution fine grid cells with a lower resolution reduced-dimension homogeneous model using averaging schemes.
Mayank Tyagi, Xu Zhou
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Analysis of CATA data by Singular Value Decomposition (SVD)

2022
_ Data by CATA (Check-All-That-Apply) method was analyzed by SVD (Singular Value Decomposition). SVD extracts row and column informations of the cross table of CATA data. An example of SVD of a cross table, which is made of kinds of rice, column variables, and of questions, row variables, produced interesting results.
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Search Result Clustering using a Singular Value Decomposition (SVD)

2009
There are many search engines in the web, but they return along list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results.
Hussam M. Dahwa Abdulla, Václav Snásel
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Reactor noise analysis based on the singular value decomposition (SVD)

Annals of Nuclear Energy, 1998
Abstract This paper reviews different techniques to analyze BWR's stability regime from neutronic power signals, and alternative methodologies based on the singular value decomposition (SVD) of a given matrix are proposed. The results obtained from experimental signals using two different constructions of the embedding space of the system have been ...
J. Navarro-Esbrí, G. Verdú, D. Ginestar, J.L. Muñoz-Cobo   +3 more
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Audio signal deblurring using singular value decomposition (SVD)

2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), 2017
Deblurring is the process of removing blurring artifacts from signals, such as blur caused by noise, defocus aberration or motion blur. Blind Convolution for signal separation is an area of research in the field of signal processing from last few decades.
Nilesh M. Patil, Milind U. Nemade
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Singular Value Decomposition (SVD)-Based Video Watermarking

2018
This chapter presents using singular value decomposition (SVD)-based video watermarking approaches. The experimental results of these approaches are also demonstrated in this chapter.
Ashish M. Kothari, Vedvyas Dwivedi, Rohit M. Thanki   +2 more
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Accelerating the Singular Value Decomposition of Rectangular Matrices with the CSX600 and the Integrable SVD

2007
We propose an approach to speed up the singular value decomposition (SVD) of very large rectangular matrices using the CSX600 floating point coprocessor. The CSX600-based acceleration board we use offers 50GFLOPS of sustained performance, which is many times greater than that provided by standard microprocessors.
Yusaku Yamamoto, Takeshi Fukaya, Takashi Uneyama, Masami Takata, Kinji Kimura, Masashi Iwasaki, Yoshimasa Nakamura   +6 more
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Development of an ASIP-based singular value decomposition processor in SVD-MIMO systems

2011 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS), 2011
In Multiple-Input Multiple-Output (MIMO) wireless systems, singular value decomposition (SVD) is used for a beamforming in SVD-MIMO systems. A beamforming can improve the performance of MIMO transmission because signal interference among antennas is suppressed.
Takaya Kaji, Shingo Yoshizawa, Yoshikazu Miyanaga   +2 more
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