Fundamentals of Numerical Computation: Julia Edition, Richard J. Braun, Tobin A. Driscoll
Автор: Hutton Название: Programming in Haskell ISBN: 1316626229 ISBN-13(EAN): 9781316626221 Издательство: Cambridge Academ Рейтинг: Цена: 49270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This edition has been extensively updated and expanded, with new chapters covering recent and more advanced features of Haskell, new examples and exercises, and freely downloadable lecture slides and example code. All concepts are explained from first principles and no programming experience is required, making it accessible to a broad range of readers.
Автор: Pozrikidis Название: Fluid Dynamics ISBN: 1489979905 ISBN-13(EAN): 9781489979902 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book provides an accessible introduction to the basic theory of fluid mechanics and computational fluid dynamics (CFD) from a modern perspective that unifies theory and numerical computation. Methods of scientific computing are introduced alongside with theoretical analysis and MATLAB® codes are presented and discussed for a broad range of topics: from interfacial shapes in hydrostatics, to vortex dynamics, to viscous flow, to turbulent flow, to panel methods for flow past airfoils.
The third edition includes new topics, additional examples, solved and unsolved problems, and revised images. It adds more computational algorithms and MATLAB programs. It also incorporates discussion of the latest version of the fluid dynamics software library FDLIB, which is freely available online. FDLIB offers an extensive range of computer codes that demonstrate the implementation of elementary and advanced algorithms and provide an invaluable resource for research, teaching, classroom instruction, and self-study.
This book is a must for students in all fields of engineering, computational physics, scientific computing, and applied mathematics. It can be used in both undergraduate and graduate courses in fluid mechanics, aerodynamics, and computational fluid dynamics. The audience includes not only advanced undergraduate and entry-level graduate students, but also a broad class of scientists and engineers with a general interest in scientific computing.
Автор: R. Albrecht; G. Alefeld; U. Kulisch; R. Grigorieff Название: Fundamentals of Numerical Computation (Computer-Oriented Numerical Analysis) ISBN: 321181566X ISBN-13(EAN): 9783211815663 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume contains mainly a collection of the invited lectures which were given during a conference on "Fundamentals of Numerical Computation," held in June, 5 - 8, 1979, on the occasion of the centennial of the Technical University of Berlin. About hundred scientists from several countries attended this conference. A preceding meeting on "Fundamentals of Computer-Arithmetic" was held in August, 1975, at the "Mathematisches Forschungsinstitut Oberwolfach." The lectures of this conference have been published as Supplementum 1 of Computing (Editors R. Albrecht, U. Kulisch). After a period of four years of active research the purpose of the Berlin-Conference was to give a broad survey of the present status of the closely connected topics Interval Analysis, Mathematical Foundation of Computer Arithmetic, Rounding Error Analysis and Stability of Numerical Algorithms and to give prospects of future activities in these fields. Besides the invited lectures 35 short com- munications, each of 20 minutes length, were given. We gratefully acknowledge the support of the President of the Technical University and of his Aussenreferat as well as of the Department of Mathematics. Besides these institutions financial support was given by AEG-Telefunken, Berlin, Allianz Lebensversicherungs A.G., Stuttgart, CDC, Hamburg/Berlin, DAT A 100, Munchen, Gesellschaft von Freunden der TU Berlin e.V., Berlin and Siemens AG., Berlin. Finally we express our thanks to Mrs. G. Froehlich and Mrs. B. Trajanovic, who managed the paper work before, during and after the conference.
Автор: Ciaramella, Gabriele Gander, Martin J. Название: Iterative methods and preconditioners for systems of linear equations ISBN: 1611976898 ISBN-13(EAN): 9781611976892 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66050.00 T Наличие на складе: Нет в наличии. Описание: Iterative methods use successive approximations to obtain more accurate solutions. Iterative Methods and Preconditioners for Systems of Linear Equationspresents historical background,derives complete convergence estimates for all methods, illustrates and provides Matlab codes for all methods, and studies and tests all preconditioners first as stationary iterative solvers.This textbook is appropriate for undergraduate and graduate students in need of an overview or of deeper knowledge about iterative methods. It can be used in courses on Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. Scientists and engineers interested in new topics and applications will also find the text useful.
Автор: Miller Название: Numerical Analysis for Engineers and Scientists ISBN: 1107021081 ISBN-13(EAN): 9781107021082 Издательство: Cambridge Academ Рейтинг: Цена: 70750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Striking a balance between theory and practice, this graduate-level text is perfect for students in the applied sciences. It provides full coverage of classical methods with a clear explanation of how they work, together with sample programs and many practical examples to help students get started.
Автор: Shen Wen Название: Introduction To Numerical Computation, An ISBN: 9814730068 ISBN-13(EAN): 9789814730068 Издательство: World Scientific Publishing Рейтинг: Цена: 53850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Developed during ten years of teaching experience, this book serves as a set of lecture notes for an introductory course on numerical computation, at the senior undergraduate level.
Автор: Paul H.C. Eilers, Brian D. Marx Название: Practical Smoothing: The Joys of P-splines ISBN: 1108482953 ISBN-13(EAN): 9781108482950 Издательство: Cambridge Academ Рейтинг: Цена: 57030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: P-splines are widely used in statistics and machine learning for smoothing out noise in data and to avoid overtraining. This practical guide covers theory and a range of standard and non-standard applications with code in R for professionals and researchers looking for a simple, flexible and powerful smoothing tool.
Автор: Gill, Philip E., Название: Numerical linear algebra and optimization / ISBN: 1611976561 ISBN-13(EAN): 9781611976564 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 74410.00 T Наличие на складе: Невозможна поставка. Описание: Numerical Linear Algebra and Optimization covers the fundamentals of closely related topics: linear systems (linear equations and least-squares) and linear programming (optimizing a linear function subject to linear constraints). For each problem class, stable and efficient numerical algorithms intended for a finite-precision environment are derived and analyzed. In 1991, when the book first appeared, these topics were rarely taught with a unified perspective, and, somewhat surprisingly, this remains true almost 30 years later. As a result, some of the material in this book can be difficult to find elsewhere—in particular, techniques for updating the LU factorization, descriptions of the simplex method applied to all-inequality form, and the analysis of what happens when using an approximate inverse to solve Ax=b.This book is appropriate for students who want to learn about numerical techniques for solving linear systems and/or linear programming using the simplex method.
Автор: Adcock, Ben Brugiapaglia, Simone Webster, Clayton G. Название: Sparse polynomial approximation of high-dimensional functions ISBN: 1611976871 ISBN-13(EAN): 9781611976878 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 70230.00 T Наличие на складе: Нет в наличии. Описание: Over seventy years ago, Richard Bellman coined the term "the curse of dimensionality" to describe phenomena and computational challenges that arise in high dimensions. These challenges, in tandem with the ubiquity of high-dimensional functions in real-world applications, have led to a lengthy, focused research effort on high-dimensional approximation—that is, the development of methods for approximating functions of many variables accurately and efficiently from data. This book provides an in-depth treatment of one of the latest installments in this long and ongoing story: sparse polynomial approximation methods. These methods have emerged as useful tools for various high-dimensional approximation tasks arising in a range of applications in computational science and engineering. It begins with a comprehensive overview of best s-term polynomial approximation theory for holomorphic, high-dimensional functions, as well as a detailed survey of applications to parametric differential equations. It then describes methods for computing sparse polynomial approximations, focusing on least squares and compressed sensing techniques.Sparse Polynomial Approximation of High-Dimensional Functions presents the first comprehensive and unified treatment of polynomial approximation techniques that can mitigate the curse of dimensionality in high-dimensional approximation, including least squares and compressed sensing. It develops main concepts in a mathematically rigorous manner, with full proofs given wherever possible, and it contains many numerical examples, each accompanied by downloadable code. The authors provide an extensive bibliography of over 350 relevant references, with an additional annotated bibliography available on the book's companion website (www.sparse-hd-book.com).This text is aimed at graduate students, postdoctoral fellows, and researchers in mathematics, computer science, and engineering who are interested in high-dimensional polynomial approximation techniques.
Автор: Claudio Canuto; M. Yousuff Hussaini; Alfio Quarter Название: Spectral Methods ISBN: 3642068006 ISBN-13(EAN): 9783642068003 Издательство: Springer Рейтинг: Цена: 104480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides the most comprehensive, up-to-date theory and state-of-the-art algorithms of spectral methods. It is written by the authors who pioneered the subject and who introduced spectral methods as a mainstream tool for scientific and engineering computation.
Автор: Dieter Heiss Название: Fundamentals of Quantum Information ISBN: 3642077722 ISBN-13(EAN): 9783642077722 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Kaizhu Huang; Amir Hussain; Qiu-Feng Wang; Rui Zha Название: Deep Learning: Fundamentals, Theory and Applications ISBN: 3030060721 ISBN-13(EAN): 9783030060725 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications.
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