A Friendly Introduction to Numerical Analysis


Author: Brian Bradie
Publisher: Prentice Hall
ISBN: 9780131911710
Category: Analyse numérique
Page: 933
View: 3229

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Designed for one or two-semester undergraduate or graduate-level courses in Numerical Analysis or Methods in mathematics departments, CS departments, and all engineering departments. This text develops concepts and techniques, followed by examples. It prepares students to use the techniques covered to solve a variety of practical problems.

A Friendly Introduction to Analysis

Single and Multivariable
Author: Witold A. J. Kosmala
Publisher: N.A
ISBN: 9780131273160
Category: Calculus
Page: 574
View: 6574

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Designed for undergraduate courses in advanced calculus and real analysis, this book is an easily readable, intimidation-free advanced calculus textbook. Ideas and methods of proof build upon each other and are explained thoroughly.

Introduction to Numerical Analysis


Author: Josef Stoer,R. Bulirsch
Publisher: Springer Science & Business Media
ISBN: 1475722729
Category: Mathematics
Page: 660
View: 1401

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On the occasion of this new edition, the text was enlarged by several new sections. Two sections on B-splines and their computation were added to the chapter on spline functions: Due to their special properties, their flexibility, and the availability of well-tested programs for their computation, B-splines play an important role in many applications. Also, the authors followed suggestions by many readers to supplement the chapter on elimination methods with a section dealing with the solution of large sparse systems of linear equations. Even though such systems are usually solved by iterative methods, the realm of elimination methods has been widely extended due to powerful techniques for handling sparse matrices. We will explain some of these techniques in connection with the Cholesky algorithm for solving positive definite linear systems. The chapter on eigenvalue problems was enlarged by a section on the Lanczos algorithm; the sections on the LR and QR algorithm were rewritten and now contain a description of implicit shift techniques. In order to some extent take into account the progress in the area of ordinary differential equations, a new section on implicit differential equa tions and differential-algebraic systems was added, and the section on stiff differential equations was updated by describing further methods to solve such equations.

Applied Numerical Analysis


Author: Gerald
Publisher: Pearson Education India
ISBN: 9788131717400
Category:
Page: 624
View: 609

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Incorporating a balance of theory with techniques and applications, this text includes optional theory-based sections. The topics, such as partial differential equations and matrix algebra, provide comprehensive and flexible coverage of all aspects of numerical analysis.

A Friendly Guide to Wavelets


Author: Gerald Kaiser
Publisher: Springer Science & Business Media
ISBN: 9780817681111
Category: Mathematics
Page: 300
View: 7043

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This volume is designed as a textbook for an introductory course on wavelet analysis and time-frequency analysis aimed at graduate students or advanced undergraduates in science and engineering. It can also be used as a self-study or reference book by practicing researchers in signal analysis and related areas. Since the expected audience is not presumed to have a high level of mathematical background, much of the needed analytical machinery is developed from the beginning. The only prerequisites for the first eight chapters are matrix theory, Fourier series, and Fourier integral transforms. Each of these chapters ends with a set of straightforward exercises designed to drive home the concepts just covered, and the many graphics should further facilitate absorption.

An Introduction to Wavelets


Author: Charles K. Chui
Publisher: Elsevier
ISBN: 1483282864
Category: Science
Page: 278
View: 3786

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Wavelet Analysis and its Applications, Volume 1: An Introduction to Wavelets provides an introductory treatise on wavelet analysis with an emphasis on spline-wavelets and time-frequency analysis. This book is divided into seven chapters. Chapter 1 presents a brief overview of the subject, including classification of wavelets, integral wavelet transform for time-frequency analysis, multi-resolution analysis highlighting the important properties of splines, and wavelet algorithms for decomposition and reconstruction of functions. The preliminary material on Fourier analysis and signal theory is covered in Chapters 2 and 3. Chapter 4 covers the introductory study of cardinal splines, while Chapter 5 describes a general approach to the analysis and construction of scaling functions and wavelets. Spline-wavelets are deliberated in Chapter 6. The last chapter is devoted to an investigation of orthogonal wavelets and wavelet packets. This volume serves as a textbook for an introductory one-semester course on “wavelet analysis for upper-division undergraduate or beginning graduate mathematics and engineering students.

Applied Numerical Linear Algebra


Author: James W. Demmel
Publisher: SIAM
ISBN: 0898713897
Category: Mathematics
Page: 419
View: 2139

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This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines.

Introduction to Statistics

Fundamental Concepts and Procedures of Data Analysis
Author: Howard M. Reid
Publisher: SAGE Publications
ISBN: 1483324281
Category: Social Science
Page: 632
View: 1920

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Using a truly accessible and reader-friendly approach, Introduction to Statistics: Fundamental Concepts and Procedures of Data Analysis, by Howard M. Reid, redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.

An Introduction to Analysis


Author: William Wade,W. R. Wade
Publisher: Math Classics
ISBN: 9780134707624
Category: Mathematics
Page: 696
View: 1594

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Originally published in 2010, reissued as part of Pearson's modern classic series.

How to Think about Analysis


Author: Lara Alcock
Publisher: Oxford University Press, USA
ISBN: 0198723539
Category: Mathematics
Page: 246
View: 1645

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Analysis is a core subject in most undergraduate mathematics degrees. It is elegant, clever and rewarding to learn, but it is hard. Even the best students find it challenging, and those who are unprepared often find it incomprehensible at first. This book aims to ensure that no student need be unprepared.

A First Course in Analysis


Author: John B. Conway
Publisher: Cambridge University Press
ISBN: 1107173140
Category: Mathematics
Page: 375
View: 4874

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This rigorous textbook is intended for a year-long analysis or advanced calculus course for advanced undergraduate or beginning graduate students. Starting with detailed, slow-paced proofs that allow students to acquire facility in reading and writing proofs, it clearly and concisely explains the basics of differentiation and integration of functions of one and several variables, and covers the theorems of Green, Gauss, and Stokes. Minimal prerequisites are assumed, and relevant linear algebra topics are reviewed right before they are needed, making the material accessible to students from diverse backgrounds. Abstract topics are preceded by concrete examples to facilitate understanding, for example, before introducing differential forms, the text examines low-dimensional examples. The meaning and importance of results are thoroughly discussed, and numerous exercises of varying difficulty give students ample opportunity to test and improve their knowledge of this difficult yet vital subject.

An Introduction to Statistical Learning

with Applications in R
Author: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
Publisher: Springer Science & Business Media
ISBN: 1461471389
Category: Mathematics
Page: 426
View: 9712

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Mathematical Logic


Author: H.-D. Ebbinghaus,J. Flum,Wolfgang Thomas
Publisher: Springer Science & Business Media
ISBN: 1475723555
Category: Mathematics
Page: 291
View: 9224

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This introduction to first-order logic clearly works out the role of first-order logic in the foundations of mathematics, particularly the two basic questions of the range of the axiomatic method and of theorem-proving by machines. It covers several advanced topics not commonly treated in introductory texts, such as Fraïssé's characterization of elementary equivalence, Lindström's theorem on the maximality of first-order logic, and the fundamentals of logic programming.

Advanced Mathematical Methods with Maple


Author: Derek Richards
Publisher: Cambridge University Press
ISBN: 9780521779814
Category: Computers
Page: 862
View: 7060

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A user-friendly student guide to computer-assisted algebra with mathematical software packages such as Maple.

Applied Numerical Methods with MATLAB for Engineers and Scientists


Author: Steven C. Chapra, Dr.
Publisher: McGraw-Hill Education
ISBN: 9780073397962
Category: Technology & Engineering
Page: 720
View: 4464

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Applied Numerical Methods with MATLAB is written for students who want to learn and apply numerical methods in order to solve problems in engineering and science. As such, the methods are motivated by problems rather than by mathematics. That said, sufficient theory is provided so that students come away with insight into the techniques and their shortcomings. McGraw-Hill Education's Connect, is also available as an optional, add on item. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, how they need it, so that class time is more effective. Connect allows the professor to assign homework, quizzes, and tests easily and automatically grades and records the scores of the student's work. Problems are randomized to prevent sharing of answers an may also have a "multi-step solution" which helps move the students' learning along if they experience difficulty.

Introduction to Information Retrieval


Author: Christopher D. Manning,Prabhakar Raghavan,Hinrich Schütze
Publisher: Cambridge University Press
ISBN: 1139472100
Category: Computers
Page: N.A
View: 9125

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Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.