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Books on the topic 'Spectra decomposition'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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1

Laberge, Gaëtan Joseph Henri. Density decomposition and energy level fluctuations in the two body random ensemble: An application to nuclear spectra. s.n.], 1989.

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2

1932-, Wang Shengwang, ed. New approaches in spectral decomposition. American Mathematical Society, 1992.

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3

1955-, Putinar Mihai, ed. Spectral decompositions and analytic sheaves. Clarendon Press, 1996.

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4

Quarteroni, Alfio. Domain decomposition preconditioners for the spectral collection method. ICASE, 1988.

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5

Kopriva, David A. Spectral solution of the viscous blunt body problem. II: Multidomain approximation. Langley Research Center, 1994.

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6

Moeglin, Colette. Spectral decomposition and Eisenstein series: Une paraphrasede l'écriture. Cambridge University Press, 1995.

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7

Quarteroni, Alfio. Domain decomposition preconditioners for the spectral collocation method. National Aeronautics and Space Administration, Langley Research Center, Institute for Computer Applications in Science and Engineering, 1988.

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8

Bachry, Andrzej. Power quality studies in distribution systems involving spectral decomposition. Otto-von-Guericke-Universität Magdeburg, 2004.

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9

Moeglin, Colette. Spectral decomposition and Eisenstein series: Une paraphrase de l'écriture. Cambridge University Press, 1995.

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10

Booß-Bavnbek, Bernhelm, Gerd Grubb, and Krzysztof P. Wojciechowski, eds. Spectral Geometry of Manifolds with Boundary and Decomposition of Manifolds. American Mathematical Society, 2005. http://dx.doi.org/10.1090/conm/366.

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11

Marianna, Bolla. Mátrixok spektrálfelbontásának és szinguláris felbontásának módszerei. Magyar Tudományos Akadémia Számítástechnikai és Automatizálási Kutató Intézete, 1985.

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12

Spectral decomposition of a covering of GL(r): The Borel case. American Mathematical Society, 2002.

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13

Theocaris, Pericles S. On a general theory of anisotropy of matter: The spectral decomposition of the compliance tensor : application to crystallography. Grapheion Dēmosieumatōn tēs Akadēmias Athēnōn, 1999.

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14

Landriani, G. Sacchi. A multidomain spectral collocation method for the Stokes problem. National Aeronautics and Space Administration, Langley Research Center, 1989.

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15

Landriani, G. Sacchi. A multidomain spectral collocation method for the Stokes problem. Institute for Computer Applications in Science and Engineering, 1989.

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16

Landriani, G. Sacchi. A multidomain spectral collocation method for the Stokes problem. National Aeronautics and Space Administration, Langley Research Center, 1989.

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17

Elsner, James B. Singular spectrum analysis: A new tool in time series analysis. Plenum Press, 1996.

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18

Tanigaki, Miho. Saturation of the approximation by spectral decompositions associated with the Schrödinger operator. Tohoku University, 1998.

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19

Tanigaki, Miho. Saturation of the approximation by spectral decompositions associated with the Schrödinger operator. Tohoku University, 1998.

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20

Souvaliotis, Athanassios. Applications of domain decomposition spectral collocation methods in viscoelastic flows through model porous media. Cornell Theory Center, Cornell University, 1992.

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21

Wong, Shek-Tung. The meromorphic continuation and functional equations of cuspidal Eisenstein series for maximal cuspidal groups. American Mathematical Society, 1990.

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22

1941-, Booss Bernhelm, Grubb Gerd, and Wojciechowski Krzysztof P. 1953-, eds. Spectral geometry of manifolds with boundary and decomposition of manifolds: Proceedings of the Workshop on Spectral Geometry of Manifolds with Boundary and Decomposition of Manifolds, Roskilde University, Roskilde, Denmark, August 6-9, 2003. American Mathematical Society, 2005.

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23

Livingston, W. C. An atlas of the solar spectrum in the infrared from 1850 to 9000 cm(-1) (1.1 to 5.4 microns): With decomposition into solar and atmospheric components and identifications of the main solar features. National Solar Observatory, 1991.

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24

Wallace, Lloyd. An atlas of the solar photospheric spectrum in the region from 8900 to 13600 cm⁻¹ (7350 to 11230 [angstroms]): With decomposition into solar and atmospheric components and identifications of the main solar features. National Solar Observatory, National Optical Astronomy Observatories, 1993.

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25

Edmunds, D. E., and W. D. Evans. Entropy Numbers, s-Numbers, and Eigenvalues. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198812050.003.0002.

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The geometric quantities entropy numbers, approximation numbers and n-widths are defined for compact linear maps, and connections with the analytic entities eigenvalues and essential spectra discussed. The celebrated inequality of Weyl between the approximation numbers and eigenvalues is established in the general context of Lorentz sequence spaces. Also included are an axiomatic approach to s-numbers, a discussion of non-compact maps, and the Schmidt decomposition theory for compact linear operators in Hilbert spaces.
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26

Moeglin, C., and J. L. Waldspurger. Decomposition Spectrale et Series d'Eisenstein (Progress in Mathematics). Birkhauser, 1993.

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27

Spectral Decomposition and Eisenstein Series: A Paraphrase of the Scriptures. Cambridge University Press, 2008.

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28

Direct-Sequence Spread-Spectrum Acoustic Communications With CRV decomposition. Storming Media, 2004.

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29

Nishith, Pallavi. Effects of alprazolam and hypnosis: EEG spectral decomposition and transient experiences. 1993.

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30

Domain decomposition methods for systems of conservation laws: Spectral collocation approximations. National Aeronautics and Space Administration, Langley Research Center, 1989.

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31

Maggiore, Michele. Gravitational Waves. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198570899.001.0001.

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A comprehensive and detailed account of the physics of gravitational waves and their role in astrophysics and cosmology. The part on astrophysical sources of gravitational waves includes chapters on GWs from supernovae, neutron stars (neutron star normal modes, CFS instability, r-modes), black-hole perturbation theory (Regge-Wheeler and Zerilli equations, Teukoslky equation for rotating BHs, quasi-normal modes) coalescing compact binaries (effective one-body formalism, numerical relativity), discovery of gravitational waves at the advanced LIGO interferometers (discoveries of GW150914, GW15122
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32

Golyandina, Nina, and Anatoly Zhigljavsky. Singular Spectrum Analysis for Time Series. Springer, 2013.

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33

Research Institute for Advanced Computer Science (U.S.), ed. A restricted signature normal form for Hermitian matrices, quasi-spectral decompositions, and applications. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1989.

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34

Zein, Fouad El, and Lˆe D˜ung Tr ´ang. Mixed Hodge Structures. Edited by Eduardo Cattani, Fouad El Zein, Phillip A. Griffiths, and Lê Dũng Tráng. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691161341.003.0003.

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This chapter discusses mixed Hodge structures (MHS). It first defines the abstract category of Hodge structures and introduces spectral sequences. The decomposition on the cohomology of Kähler manifolds is used to prove the degeneration at rank 1 of the spectral sequence defined by the filtration F on the de Rham complex in the projective nonsingular case. The chapter then introduces an abstract definition of MHS as an object of interest in linear algebra. It then attempts to develop algebraic homology techniques on filtered complexes up to filtered quasi-isomorphisms of complexes. Finally, th
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35

Moeglin, C. Decomposition Spectrale Et Series D'Eisenestein: Une Paraphase De L'Ecriture (Progress in Mathematics Series Vol 113). Birkhauser, 1994.

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36

Chen, Hao. The inhibitory effect of water on the decomposition of methyl linoleate hydroperoxides in a model system using NMR spectroscopy. 1989.

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37

Kaye, Phillip, Raymond Laflamme, and Michele Mosca. An Introduction to Quantum Computing. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780198570004.001.0001.

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This concise, accessible text provides a thorough introduction to quantum computing - an exciting emergent field at the interface of the computer, engineering, mathematical and physical sciences. Aimed at advanced undergraduate and beginning graduate students in these disciplines, the text is technically detailed and is clearly illustrated throughout with diagrams and exercises. Some prior knowledge of linear algebra is assumed, including vector spaces and inner products. However, prior familiarity with topics such as tensor products and spectral decomposition is not required, as the necessary
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38

Bouchaud, Jean-Philippe. Random matrix theory and (big) data analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797319.003.0006.

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This chapter reviews methods from random matrix theory to extract information about a large signal matrix C (for example, a correlation matrix arising in big data problems), from its noisy observation matrix M. The chapter shows that the replica method can be used to obtain both the spectral density and the overlaps between noise-corrupted eigenvectors and the true ones, for both additive and multiplicative noise. This allows one to construct optimal rotationally invariant estimators of C based on the observation of M alone. This chapter also discusses the case of rectangular correlation matri
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39

Schacher, Jan C. Algorithmic Spatialization. Edited by Roger T. Dean and Alex McLean. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.013.12.

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Beginning with a brief historical overview of spatial audio and music practices, this chapter looks at principles of sound spatialization, algorithms for composing and rendering spatial sound and music, and different techniques of spatial source positioning and sound space manipulation. These operations include composing with abstract objects in a sound scene, creating compound sounds using source clusters, altering spatial characteristics by means of spectral sound decomposition, and the manipulation of artificial acoustic spaces. The chapter goes on to discuss practical issues of live spatia
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40

Huybrechts, D. Spherical and Exceptional Objects. Oxford University Press, 2007. http://dx.doi.org/10.1093/acprof:oso/9780199296866.003.0008.

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Spherical objects — motivated by considerations in the context of mirror symmetry — are used to construct special autoequivalences. Their action on cohomology can be described precisely, considering more than one spherical object often leads to complicated (braid) groups acting on the derived category. The results related to Beilinson are almost classical. Section 3 of this chapter gives an account of the Beilinson spectral sequence and how it is used to deduce a complete description of the derived category of the projective space. This will use the language of exceptional sequences and semi-o
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41

Zabrodin, Anton. Financial applications of random matrix theory: a short review. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.40.

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This article reviews some applications of random matrix theory (RMT) in the context of financial markets and econometric models, with emphasis on various theoretical results (for example, the Marčenko-Pastur spectrum and its various generalizations, random singular value decomposition, free matrices, largest eigenvalue statistics) as well as some concrete applications to portfolio optimization and out-of-sample risk estimation. The discussion begins with an overview of principal component analysis (PCA) of the correlation matrix, followed by an analysis of return statistics and portfolio theor
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