Journal Of Approximation Theory And Applied Mathematics 2013 Vol 1 And
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| Author | : Marco Schuchmann |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 110 |
| Release | : 2014-04-10 |
| Genre | : Mathematics |
| ISBN | : 3735791859 |
Journal of Approximation Theory and Applied Mathematics (ISSN 2196-1581) is a journal which started in 2013. Themes of our journal are: Approximation theory (with a focus on wavelets) and applications in mathematics like numerical analysis, statistics or financial mathematics. Contents 2013 Vol. 1: An Approximation on a Compact Interval Calculated with a Wavelet Collocation Method can Lead to Much Better Results than other Methods, Parameter Identification with a Wavelet Collocation Method in a Partial Differential Equation, An Approach for a Parameter Estimation with a Wavelet Collocation Method, Notes on Nonparametric Regression with Wavelets, Extrapolation and Approximation with a Wavelet Collocation Method for ODEs 2013 Vol. 2: Solving ODEs and DAEs with a Wavelet Collocation Method with Examples from the Chemical Reaction Kinetics, Solving Integral Equations with a Wavelet Collocation Approach, Approximation of Non L2(R) Functions on a Compact Interval with a Wavelet Base, Comparing Approximations of a Wavelet Collocation Method of Various Wavelets
| Author | : George A. Anastassiou |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2013-04-26 |
| Genre | : Mathematics |
| ISBN | : 9781461463924 |
Advances in Applied Mathematics and Approximation Theory: Contributions from AMAT 2012 is a collection of the best articles presented at “Applied Mathematics and Approximation Theory 2012,” an international conference held in Ankara, Turkey, May 17-20, 2012. This volume brings together key work from authors in the field covering topics such as ODEs, PDEs, difference equations, applied analysis, computational analysis, signal theory, positive operators, statistical approximation, fuzzy approximation, fractional analysis, semigroups, inequalities, special functions and summability. The collection will be a useful resource for researchers in applied mathematics, engineering and statistics.
| Author | : Armin Iske |
| Publisher | : Springer |
| Total Pages | : 363 |
| Release | : 2018-12-14 |
| Genre | : Mathematics |
| ISBN | : 3030052281 |
This textbook offers an accessible introduction to the theory and numerics of approximation methods, combining classical topics of approximation with recent advances in mathematical signal processing, and adopting a constructive approach, in which the development of numerical algorithms for data analysis plays an important role. The following topics are covered: * least-squares approximation and regularization methods * interpolation by algebraic and trigonometric polynomials * basic results on best approximations * Euclidean approximation * Chebyshev approximation * asymptotic concepts: error estimates and convergence rates * signal approximation by Fourier and wavelet methods * kernel-based multivariate approximation * approximation methods in computerized tomography Providing numerous supporting examples, graphical illustrations, and carefully selected exercises, this textbook is suitable for introductory courses, seminars, and distance learning programs on approximation for undergraduate students.
| Author | : Joseph Suresh Paul |
| Publisher | : CRC Press |
| Total Pages | : 306 |
| Release | : 2019-11-05 |
| Genre | : Medical |
| ISBN | : 1351029258 |
Regularization becomes an integral part of the reconstruction process in accelerated parallel magnetic resonance imaging (pMRI) due to the need for utilizing the most discriminative information in the form of parsimonious models to generate high quality images with reduced noise and artifacts. Apart from providing a detailed overview and implementation details of various pMRI reconstruction methods, Regularized image reconstruction in parallel MRI with MATLAB examples interprets regularized image reconstruction in pMRI as a means to effectively control the balance between two specific types of error signals to either improve the accuracy in estimation of missing samples, or speed up the estimation process. The first type corresponds to the modeling error between acquired and their estimated values. The second type arises due to the perturbation of k-space values in autocalibration methods or sparse approximation in the compressed sensing based reconstruction model. Features: Provides details for optimizing regularization parameters in each type of reconstruction. Presents comparison of regularization approaches for each type of pMRI reconstruction. Includes discussion of case studies using clinically acquired data. MATLAB codes are provided for each reconstruction type. Contains method-wise description of adapting regularization to optimize speed and accuracy. This book serves as a reference material for researchers and students involved in development of pMRI reconstruction methods. Industry practitioners concerned with how to apply regularization in pMRI reconstruction will find this book most useful.
| Author | : Maïtine Bergounioux |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 540 |
| Release | : 2017-01-11 |
| Genre | : Mathematics |
| ISBN | : 3110430398 |
With a focus on the interplay between mathematics and applications of imaging, the first part covers topics from optimization, inverse problems and shape spaces to computer vision and computational anatomy. The second part is geared towards geometric control and related topics, including Riemannian geometry, celestial mechanics and quantum control. Contents: Part I Second-order decomposition model for image processing: numerical experimentation Optimizing spatial and tonal data for PDE-based inpainting Image registration using phase・amplitude separation Rotation invariance in exemplar-based image inpainting Convective regularization for optical flow A variational method for quantitative photoacoustic tomography with piecewise constant coefficients On optical flow models for variational motion estimation Bilevel approaches for learning of variational imaging models Part II Non-degenerate forms of the generalized Euler・Lagrange condition for state-constrained optimal control problems The Purcell three-link swimmer: some geometric and numerical aspects related to periodic optimal controls Controllability of Keplerian motion with low-thrust control systems Higher variational equation techniques for the integrability of homogeneous potentials Introduction to KAM theory with a view to celestial mechanics Invariants of contact sub-pseudo-Riemannian structures and Einstein・Weyl geometry Time-optimal control for a perturbed Brockett integrator Twist maps and Arnold diffusion for diffeomorphisms A Hamiltonian approach to sufficiency in optimal control with minimal regularity conditions: Part I Index
| Author | : Rassul Bairamkulov |
| Publisher | : Springer Nature |
| Total Pages | : 356 |
| Release | : 2022-11-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3031110471 |
Networks are pervasive. Very large scale integrated (VLSI) systems are no different, consisting of dozens of interconnected subsystems, hundreds of modules, and many billions of transistors and wires. Graph theory is crucial for managing and analyzing these systems. In this book, VLSI system design is discussed from the perspective of graph theory. Starting from theoretical foundations, the authors uncover the link connecting pure mathematics with practical product development. This book not only provides a review of established graph theoretic practices, but also discusses the latest advancements in graph theory driving modern VLSI technologies, covering a wide range of design issues such as synchronization, power network models and analysis, and interconnect routing and synthesis. Provides a practical introduction to graph theory in the context of VLSI systems engineering; Reviews comprehensively graph theoretic methods and algorithms commonly used during VLSI product development process; Includes a review of novel graph theoretic methods and algorithms for VLSI system design.
| Author | : Steve Zelditch |
| Publisher | : American Mathematical Soc. |
| Total Pages | : 410 |
| Release | : 2017-12-12 |
| Genre | : Mathematics |
| ISBN | : 1470410370 |
Eigenfunctions of the Laplacian of a Riemannian manifold can be described in terms of vibrating membranes as well as quantum energy eigenstates. This book is an introduction to both the local and global analysis of eigenfunctions. The local analysis of eigenfunctions pertains to the behavior of the eigenfunctions on wavelength scale balls. After re-scaling to a unit ball, the eigenfunctions resemble almost-harmonic functions. Global analysis refers to the use of wave equation methods to relate properties of eigenfunctions to properties of the geodesic flow. The emphasis is on the global methods and the use of Fourier integral operator methods to analyze norms and nodal sets of eigenfunctions. A somewhat unusual topic is the analytic continuation of eigenfunctions to Grauert tubes in the real analytic case, and the study of nodal sets in the complex domain. The book, which grew out of lectures given by the author at a CBMS conference in 2011, provides complete proofs of some model results, but more often it gives informal and intuitive explanations of proofs of fairly recent results. It conveys inter-related themes and results and offers an up-to-date comprehensive treatment of this important active area of research.
| Author | : Robert M. Corless |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 896 |
| Release | : 2013-12-12 |
| Genre | : Mathematics |
| ISBN | : 1461484537 |
This book provides an extensive introduction to numerical computing from the viewpoint of backward error analysis. The intended audience includes students and researchers in science, engineering and mathematics. The approach taken is somewhat informal owing to the wide variety of backgrounds of the readers, but the central ideas of backward error and sensitivity (conditioning) are systematically emphasized. The book is divided into four parts: Part I provides the background preliminaries including floating-point arithmetic, polynomials and computer evaluation of functions; Part II covers numerical linear algebra; Part III covers interpolation, the FFT and quadrature; and Part IV covers numerical solutions of differential equations including initial-value problems, boundary-value problems, delay differential equations and a brief chapter on partial differential equations. The book contains detailed illustrations, chapter summaries and a variety of exercises as well some Matlab codes provided online as supplementary material. “I really like the focus on backward error analysis and condition. This is novel in a textbook and a practical approach that will bring welcome attention." Lawrence F. Shampine A Graduate Introduction to Numerical Methods and Backward Error Analysis” has been selected by Computing Reviews as a notable book in computing in 2013. Computing Reviews Best of 2013 list consists of book and article nominations from reviewers, CR category editors, the editors-in-chief of journals, and others in the computing community.
| Author | : Robert Qiu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 633 |
| Release | : 2013-08-04 |
| Genre | : Technology & Engineering |
| ISBN | : 1461445442 |
Wireless Distributed Computing and Cognitive Sensing defines high-dimensional data processing in the context of wireless distributed computing and cognitive sensing. This book presents the challenges that are unique to this area such as synchronization caused by the high mobility of the nodes. The author will discuss the integration of software defined radio implementation and testbed development. The book will also bridge new research results and contextual reviews. Also the author provides an examination of large cognitive radio network; hardware testbed; distributed sensing; and distributed computing.
| Author | : Hans-Joachim Bungartz |
| Publisher | : Springer Nature |
| Total Pages | : 268 |
| Release | : 2022-03-14 |
| Genre | : Mathematics |
| ISBN | : 3030813622 |
Sparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different flavors, are frequently the method of choice. This volume of LNCSE presents selected papers from the proceedings of the fifth workshop on sparse grids and applications, and demonstrates once again the importance of this numerical discretization scheme. The articles present recent advances in the numerical analysis of sparse grids in connection with a range of applications including uncertainty quantification, plasma physics simulations, and computational chemistry, to name but a few.
