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標(biāo)題: Titlebook: Implementing Spectral Methods for Partial Differential Equations; Algorithms for Scien David A. Kopriva Book 2009 Springer Science+Business [打印本頁]

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David A. Koprivaial markers. In marker-less feature-based tracking salient regions in the images are identified by the detector and information about these regions are extracted and stored by the descriptor for matching. Speeded-Up Robust Feature (SURF) is considered as the most robust detector and descriptor so fa
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David A. Koprivaough there would be much disagreement as to the exact proportion of papers published in developmental journals that could be considered cognitive, 50% seems like a conservative estimate. Hence, a series of scholarly books devoted to work in cognitive development is especially appropriate at this tim
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David A. Koprivat. Socrates wondered how an ignorant shepherd boy could manipulate objects as if he were aware of their geometric properties. The larger question was how we come to know anything when we do not already know it. The problem rests in the perception that there is a subjective ‘I’, or person, looking ou
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Algorithms for Non-Periodic Functionse the Legendre and Chebyshev polynomials themselves. Those algorithms are then used to compute the Gauss quadrature nodes and weights that are needed in turn to compute interpolants and discrete inner products. The chapter ends with algorithms used to approximate the derivatives that appear in PDEs
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Survey of Spectral ApproximationsThe methods developed are the Fourier collocation and Galerkin methods, polynomial collocation and Galerkin methods, and nodal continuous and discontinuous Galerkin methods. At the end of the chapter, after it is clear what the methods are, how they are derived, and how they are implemented, a discu
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Spectral Methods in Non-Square Geometriesoblems on quadrilateral domains. Benchmark solutions include potentials in non-square domains, incompressible flow over a circular obstacle, potential in an annulus, advection-diffusion in curved channels, and acoustic scattering off a cylinder.
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Spectral Element Methodsn spectral methods, and spectral element methods in particular, the domain of interest is subdivided into smaller subdomains that are mapped individually onto the square, allowing problems in truly complex geometries to be solved. Spectral element methods are introduced for one space dimension then
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978-90-481-8484-2Springer Science+Business Media B.V. 2009
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Implementing Spectral Methods for Partial Differential Equations978-90-481-2261-5Series ISSN 1434-8322 Series E-ISSN 2198-2589
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David A. KoprivaFirst book to cover multidomain spectral methods for the numerical solution of time-dependent 1D and 2D partial differential equations.Presented without too much abstract mathematics and minutae.Conta
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Scientific Computationhttp://image.papertrans.cn/i/image/462650.jpg
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https://doi.org/10.1007/978-90-481-2261-5Approximation of Derivatives; FFT Algorithm; Implementation of Spectral Methods; Multidomain Spectral M
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Algorithms for Periodic Functions, the transforms are sped up by about a factor of two by exploiting symmetries in the data and the coefficients. The chapter ends with how to approximate the derivatives of periodic functions, thus presenting the fundamental algorithms that are needed to solve partial differential equations with periodic boundary conditions.
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Survey of Spectral ApproximationsThe methods developed are the Fourier collocation and Galerkin methods, polynomial collocation and Galerkin methods, and nodal continuous and discontinuous Galerkin methods. At the end of the chapter, after it is clear what the methods are, how they are derived, and how they are implemented, a discussion is presented on how to choose between them.
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1434-8322 ose algorithms to solve steady and time dependent PDEs in one and two space dimensions. Exercises and questions at the?end of each chapter encourage the reader to experiment with the?algorithms..978-90-481-8484-2978-90-481-2261-5Series ISSN 1434-8322 Series E-ISSN 2198-2589
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David A. Koprivassions. In addition, the small cell performs an appropriate resource allocation process for its UE to increase its communication capacity. The MuSiC algorithm is used to estimate the DoAs of the UE signal replicas in an indoor environment, assuming a variable number of multipath components that are
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David A. Koprivaltering techniques can be adapted for noise declining to improve the visual quality as well as a reorganization of images. Here four types of noises have been undertaken and applied to process images. Besides linear and nonlinear filtering methods like Gaussian filter, median filter, mean filter and
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David A. Koprivaoducts of the subjective mind. We might conclude then that it was meaningless to talk of an objective reality because we could never cognitively manipulate it. But this view leads to a logical nonsense where, because reality would be constructed by the subjective mind, it would always be fashioned b
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Book 2009rature algorithms, and how to approximate derivatives. The second?part shows how to use those algorithms to solve steady and time dependent PDEs in one and two space dimensions. Exercises and questions at the?end of each chapter encourage the reader to experiment with the?algorithms..
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David A. Koprivaress volumes will be edited collections. Editors of such collections, upon consultation with the Series Editor, may elect to have their books published either a978-1-4613-9546-1978-1-4613-9544-7Series ISSN 1431-8555




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