Автор: Burden Annette, Burden Richard, Faires J. Douglas Название: Numerical analysis ISBN: 1305253663 ISBN-13(EAN): 9781305253667 Издательство: Cengage Learning Рейтинг: Цена: 62820.00 T Наличие на складе: Есть Описание: Introduces readers to the theory and application of modern numerical approximation techniques. Providing an accessible treatment that only requires a calculus prerequisite, the authors explain how, why, and when approximation techniques can be expected to work - and why, in some situations, they fail.
Автор: Lloyd N. Trefethen Название: Approximation Theory and Approximation Practice: Extended Edition ISBN: 161197593X ISBN-13(EAN): 9781611975932 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 60990.00 T Наличие на складе: Поставка под заказ. Описание: This is a textbook on classical polynomial and rational approximation theory for the twenty-first century. Aimed at advanced undergraduates and graduate students across all of applied mathematics, it uses MATLAB to teach the field’s most important ideas and results.
Approximation Theory and Approximation Practice, Extended Edition differs fundamentally from other works on approximation theory in a number of ways: its emphasis is on topics close to numerical algorithms; concepts are illustrated with Chebfun; and each chapter is a PUBLISHable MATLAB M-file, available online.
The book centers on theorems and methods for analytic functions, which appear so often in applications, rather than on functions at the edge of discontinuity with their seductive theoretical challenges. Original sources are cited rather than textbooks, and each item in the bibliography is accompanied by an editorial comment. In addition, each chapter has a collection of exercises, which span a wide range from mathematical theory to Chebfun-based numerical experimentation.
Автор: John M. Stewart Название: Python for Scientists ISBN: 1316641236 ISBN-13(EAN): 9781316641231 Издательство: Cambridge Academ Рейтинг: Цена: 33780.00 T Наличие на складе: Поставка под заказ. Описание: Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.
Автор: Deng Weihua Название: Modeling Anomalous Diffusion: From Statistics To Mathematics ISBN: 9811212996 ISBN-13(EAN): 9789811212994 Издательство: World Scientific Publishing Рейтинг: Цена: 95040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book focuses on modeling the anomalous diffusion phenomena, being ubiquitous in the natural world. Both the microscopic models (stochastic processes) and macroscopic models (partial differential equations) have been built up. The relationships between the two kinds of models are clarified, and based on these models, some statistical observables are analyzed. From statistics to mathematics, the built models show their power with their associated applications.
This book is important for students to develop basic skills to be able to succeed in their future research. In addition to introducing the related models or methods, it also provides the corresponding applications and simulation results, which will attract more readers ranging from mathematicians to physicists or chemists, to name a few.
Автор: Brezinski, Claude, Название: Biorthogonality and its applications to numerical analysis / ISBN: 0824786165 ISBN-13(EAN): 9780824786168 Издательство: Taylor&Francis Рейтинг: Цена: 234790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explores the use of the concept of biorthogonality and discusses the various recurrence relations for the generalizations of the method of moments, the method of Lanczos, and the biconjugate gradient method. It is helpful for researchers in numerical analysis and approximation theory.
Автор: V.B.K. Vatti Название: Numerical Analysis: Iterative Methods ISBN: 9385909002 ISBN-13(EAN): 9789385909009 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 64680.00 T Наличие на складе: Невозможна поставка. Описание: Iterative methods or those methods by which approximations are improved until one receives an accurate value comprise an important learning objective in mathematics. The primary objective of this book is to incorporate important iterative methods in a single volume to enable students and researchers to apply iterative techniques to scientific and engineering problems.
Автор: David L. Chopp Название: Introduction to High Performance Scientific Computing ISBN: 1611975638 ISBN-13(EAN): 9781611975635 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 76910.00 T Наличие на складе: Поставка под заказ. Описание: Based on a course developed by the author, Introduction to High Performance Scientific Computing introduces methods for adding parallelism to numerical methods for solving differential equations. It contains exercises and programming projects that facilitate learning as well as examples and discussions based on the C programming language, with additional comments for those already familiar with C . The text provides an overview of concepts and algorithmic techniques for modern scientific computing and is divided into six self-contained parts that can be assembled in any order to create an introductory course using available computer hardware.Part I introduces the C programming language for those not already familiar with programming in a compiled language. Part II describes parallelism on shared memory architectures using OpenMP. Part III details parallelism on computer clusters using MPI for coordinating a computation. Part IV demonstrates the use of graphical programming units (GPUs) to solve problems using the CUDA language for NVIDIA graphics cards. Part V addresses programming on GPUs for non-NVIDIA graphics cards using the OpenCL framework. Finally, Part VI contains a brief discussion of numerical methods and applications, giving the reader an opportunity to test the methods on typical computing problems. Introduction to High Performance Scientific Computing is intended for advanced undergraduate or beginning graduate students who have limited exposure to programming or parallel programming concepts. Extensive knowledge of numerical methods is not assumed. The material can be adapted to the available computational hardware, from OpenMP on simple laptops or desktops to MPI on computer clusters or CUDA and OpenCL for computers containing NVIDIA or other graphics cards. Experienced programmers unfamiliar with parallel programming will benefit from comparing the various methods to determine the type of parallel programming best suited for their application. The book can be used for courses on parallel scientific computing, high performance computing, and numerical methods for parallel computing.
Domain decomposition (DD) methods provide powerful tools for constructing parallel numerical solution algorithms for large scale systems of algebraic equations arising from the discretization of partial differential equations. These methods are well-established and belong to a fast developing area. In this volume, the reader will find a brief historical overview, the basic results of the general theory of domain and space decomposition methods as well as the description and analysis of practical DD algorithms for parallel computing. It is typical to find in this volume that most of the presented DD solvers belong to the family of fast algorithms, where each component is efficient with respect to the arithmetical work. Readers will discover new analysis results for both the well-known basic DD solvers and some DD methods recently devised by the authors, e.g., for elliptic problems with varying chaotically piecewise constant orthotropism without restrictions on the finite aspect ratios.
The hp finite element discretizations, in particular, by spectral elements of elliptic equations are given significant attention in current research and applications. This volume is the first to feature all components of Dirichlet-Dirichlet-type DD solvers for hp discretizations devised as numerical procedures which result in DD solvers that are almost optimal with respect to the computational work. The most important DD solvers are presented in the matrix/vector form algorithms that are convenient for practical use.
Автор: Vetterli Название: Foundations of Signal Processing ISBN: 110703860X ISBN-13(EAN): 9781107038608 Издательство: Cambridge Academ Рейтинг: Цена: 69690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This comprehensive, accessible textbook covers the basics of signal processing, building up from fundamental principles to practical applications. It uses engineering notation to make mathematical concepts easy to follow, includes numerous homework problems and is accompanied by an extensive Mathematica (R) companion and instructor solutions manual.
Автор: Bernard J. Geurts Название: Direct and Large-Eddy Simulation ISBN: 3110516217 ISBN-13(EAN): 9783110516210 Издательство: Walter de Gruyter Цена: 173490.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The series is devoted to the publication of high-level monographs and specialized graduate texts which cover the modern mathematical foundations behind computational science and its applications in physical and life sciences, and in engineering.
One of its main objectives is to make available to the professional community expositions of results and in-depth presentation of techniques that are of current importance to technological and practical applications.
Автор: Al-Baali Mehiddin, Purnama Anton, Grandinetti Lucio Название: Numerical Analysis and Optimization: Nao-V, Muscat, Oman, January 2020 ISBN: 303072039X ISBN-13(EAN): 9783030720391 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A new inexact nonmonotone filter sequential quadratic programming algorithm (Mahdavi-Amiri et al.).- Behavior of Limited Memory BFGS when Applied to Nonsmooth Functions and their Nesterov Smoothings(Overton et al.).- Subgradient smoothing method for nonsmooth nonconvex optimization(Roos et al.).- On some optimization problems that can be solved in O(n) time(Facchinei et al.).- Iteration complexity of a fixed-stepsize SQP method for nonconvex optimization with convex constraints(Facchinei et al.).- Modelling and Inferring the Triggering Function in a Self-Exciting Point Process(Mahdavi-Amiri et al.).- A new multi-point stepsize gradient method for optimization(Higham et al.).- A Julia implementation of Algorithm NCL for constrained optimization(Dai et al.).- A Survey on Modeling Approaches for Generation and Transmission Expansion Planning Analysis (Vespucci et al.).- Second Order Adjoints in Optimization (Sachs).- Largest Small n-polygons: Numerical Optimum Estimates for n >= 6 (Pintйr).- Computational Science in the 17th century. Numerical solution of algebraic equations: digit-by-digit computation (Steihaug).
Автор: Martin J. Gander, Felix Kwok Название: Numerical Analysis of Partial Differential Equations Using Maple and MATLAB ISBN: 1611975301 ISBN-13(EAN): 9781611975307 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 56850.00 T Наличие на складе: Невозможна поставка. Описание: This book provides an elementary yet comprehensive introduction to the numerical solution of partial differential equations (PDEs). Used to model important phenomena, such as the heating of apartments and the behavior of electromagnetic waves, these equations have applications in engineering and the life sciences, and most can only be solved approximately using computers.Numerical Analysis of Partial Differential Equations Using Maple and MATLAB provides detailed descriptions of the four major classes of discretization methods for PDEs (finite difference method, finite volume method, spectral method, and finite element method) and runnable MATLAB® code for each of the discretization methods and exercises. It also gives self-contained convergence proofs for each method using the tools and techniques required for the general convergence analysis but adapted to the simplest setting to keep the presentation clear and complete.This book is intended for advanced undergraduate and early graduate students in numerical analysis and scientific computing and researchers in related fields. It is appropriate for a course on numerical methods for partial differential equations.
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