MuPAD Multi Processing Algebra Data Tool, FUCHSSTEINER; WIWIANKA
Автор: Benno Fuchssteiner; Klaus Gottheil; Andreas Kemper Название: MuPAD ISBN: 3764350172 ISBN-13(EAN): 9783764350178 Издательство: Springer Рейтинг: Цена: 74490.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: MuPAD is a parallel-processing general purpose computer algebra system. This tutorial provides an introduction to MuPAD and is addressed to beginners in computer algebra as well as advanced users. It encourages users to get to know MuPAD through "learning-by-doing".
Part I: Mathematical Foundations: 1 Cem Yolcu and Evren Цzarslan: Diffusion-Weighted Magnetic Resonance Signal for General Gradient Waveforms: Multiple Correlation Function Framework, Path Integrals, and Parallels Between Them.- 2 T.C.J. Dela Haije, A. Fuster and L.M.J. Florack: Finslerian Diffusion and the Bloch-Torrey Equation.- 3 M. Moakher and P. J. Basser: Fiber Orientation Distribution Functions and Orientation Tensors for Different Material Symmetries.- 4 Yue Zhang, Jonathan Palacios and Eugene Zhang: Topology of 3D Linear Symmetric Tensor Fields.- 5 Carmeliza Navasca and Deonnia N. Pompey: Random Projections for Low Multilinear Rank Tensors.- Part II: Processing, Filtering and Interpolation: 6Jasper J. van de Gronde, Mikola Lysenko and Jos B.T.M. Roerdink: Path-Based Mathematical Morphology on Tensor Fields.- 7 Andreas Kleefeld and Bernhard Burgeth: Processing Multispectral Images via Mathematical Morphology.- 8 Luc Florack, Tom Dela Haije and Andrea Fuster: Direction-Controlled DTI Interpolation.- 9 Daniel Jцrgens and Rodrigo Moreno: Tensor Voting: Current State, Challenges and New Trends in the Context of Medical Image Analysis.- Part III: Visualization: 10 Olivier Vaillancourt, Maxime Chamberland, Jean-Christophe Houde and Maxime Descoteaux: Visualization of Diffusion Propagator and Multiple Parameter Diffusion Signal.- 11 Sujal Bista, Jiachen Zhuo, Rao P. Gullapalli and Amitabh Varshney: Visual Knowledge Discovery for Diffusion Kurtosis Datasets of the Human Brain.- 12 Tobias Isenberg: A Survey of Illustrative Visualization Techniques for Diffusion-Weighted MRI Tractography.- 13 Valentin Zobel, Jan Reininghaus and Ingrid Hotz: Visualizing Symmetric Indefinite 2D Tensor Fields Using the Heat Kernel Signature.- Part IV: Statistical Analysis: 14 Maxime Taquet, Benoit Scherrer and Simon K. Warfield: A Framework for the Analysis of Diffusion Compartment Imaging (DCT).- 15 Lauren J. O'Donnell and Thomas Schultz: Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Diffusion Imaging Data.- Part V: Applications: 16 A. Maries, T. Luciani, P.H. Pisciuneri, M.B. Nik, S.L. Yilmaz, P. Givi and G.E. Marai: A Clustering Method for Identifying Regions of Interest in Turbulent Combustion Tensor Fields.- 17 Mark Schцneich, Andrea Kratz, Valentin Zobel, Gerik Scheuermann, Markus Stommel, and Ingrid Hotz: Tensor Lines in Engineering - Success, Failure, and Open Questions.- 18 Vesna Prchkovska, Magн Andorrа, Pablo Villoslada, Eloy Martinez-Heras, Remco Duits, David Fortin, Paulo Rodrigues and Maxime Descoteaux: Contextual Diffusion Image Post-Processing Aids Clinical Applications.
Автор: Adam Bojanczyk; George Cybenko Название: Linear Algebra for Signal Processing ISBN: 0387944915 ISBN-13(EAN): 9780387944913 Издательство: Springer Рейтинг: Цена: 204040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Gives particular emphasis to exposing contexts of the signal processing problems so that the impact of algorithms and hardware can be understood.This book brings together the writings of signal processing engineers, computer engineers, and applied linear algebraists in an exchange of problems, theories, and techniques.
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