Concrete Mathematics: A Foundation for Computer Science 2e

Concrete Mathematics: A Foundation for Computer Science 2nd Edition PDF Download Ebook. Ronald L. Graham, Donald E. Knuth and Oren Patashnik introduce the mathematics that supports advanced computer programming and the analysis of algorithms.

The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data. It is an indispensable text and reference not only for computer scientists - the authors themselves rely heavily on it! - but for serious users of mathematics in virtually every discipline.

This text is a blending of CONtinuous and disCRETE mathematics. "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems." The subject matter is primarily an expansion of the Mathematical Preliminaries section in Knuth's classic Art of Computer Programming, but the style of presentation is more leisurely, and individual topics are covered more deeply.

Several new topics have been added, and the most significant ideas have been traced to their historical roots. The book includes more than 500 exercises, divided into six categories. Complete answers are provided for all exercises, except research problems, making the book particularly valuable for self-study.

This second edition includes important new material about mechanical summation. In response to the widespread use of the first edition as a reference book, the bibliography and index have also been expanded, and additional nontrivial improvements can be found on almost every page. Readers will appreciate the informal style of Concrete Mathematics. Particularly enjoyable are the marginal graffiti contributed by students who have taken courses based on this material. The authors want to convey not only the importance of the techniques presented, but some of the fun in learning and using them.

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The Art of R Programming: A Tour of Statistical Software Design

The Art of R Programming: A Tour of Statistical Software Design PDF Download Ebook. Norman Matloff takes on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro.

Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to create artful graphs to visualize complex data sets and functions, write more efficient code using parallel R and vectorization.

Readers also shows guidelines to interface R with C/C++ and Python for increased speed or functionality, find new packages for text analysis, image manipulation, and thousands more to squash annoying bugs with advanced debugging techniques. Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, this is your guide to harnessing the power of statistical computing.

In addition to providing statistical operations, R is a general-purpose programming language, so you can use it to automate analyses and create new functions that extend the existing language features. R includes a library of several thousand user-contributed packages. It incorporates features found in object-oriented and functional programming languages. R is capable of producing beautiful graphics for your presentations, reports or articles.

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Numerical Methods Using Matlab 4th Edition, Mathews

Numerical Methods Using Matlab 4th Edition PDF Download Ebook. John H. Mathews and Kurtis K. Fink provide fundamental introduction to numerical analysis suitable for undergraduate students in mathematics, computer science, physical sciences, and engineering. It is assumed that the reader is familiar with calculus and has taken a structured programming course. The text has enough material fitted modularly for either a single-term course or a year sequence. In short, the book contains enough material so that instructors will be able to select topics appropriate to their needs.

Students of various backgrounds should find numerical methods quite interesting and useful, and this is kept in mind throughout the book. Thus, there is a wide variety of examples and problems that help to sharpen one's skill in both the theory and practice of numerical analysis. Computer calculations are presented in the form of tables and graphs whenever possible so that the resulting numerical approximations are easier to visualize and interpret. MATLAB programs are the vehicle for presenting the underlying numerical algorithms.

Emphasis is placed on understanding why numerical methods work and their limitations. This is challenging and involves a balance between theory, error analysis, and readability. An error analysis for each method is presented in a fashion that is appropriate for the method at hand, yet does not turn off the reader. A mathematical derivation for each method is given that uses elementary results and builds the student's understanding of calculus. Computer assignments using MATLAB give students an opportunity to practice their skills at scientific programming.

Shorter numerical exercises can be carried out with a pocket calculator/computer, and the longer ones can be done using MATLAB subroutinie libraries. It is left for the instructor to guide the students regarding the pedagogical use of numerical computations. Each instructor can make assignments that are appropriate to the available computing resources. Experimentation with the MATLAB subroutine libraries is encouraged. These materials can be used to assist students in the completion of the numerical analysis component of computer laboratory exercises.

In this edition a section on Bezier curves has been added to the end of the chapter on curve fitting. Additionally, the chapter on numerical optimization has been expanded to include an introduction to both direct and derivative based methods for optimizing functions of one or more variables.

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Numerical Methods in Finance and Economics: A MATLAB-Based Introduction

Numerical Methods in Finance and Economics: A MATLAB-Based Introduction 2nd Edition PDF Download Ebook. Paolo Brandimarte describes state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance. The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance.

Reflecting this development, this book bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB®—the powerful numerical computing environment—for financial applications. The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives.

A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions. Among this book's most outstanding features is the integration of MATLAB®, which helps students and practitioners solve relevant problems in finance, such as portfolio management and derivatives pricing.

This tutorial is useful in connecting theory with practice in the application of classical numerical methods and advanced methods, while illustrating underlying algorithmic concepts in concrete terms. This book presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPL©, to connect the pencil-and-paper statement of an optimization model with its solution by a software library. Offering computational practice in both financial engineering and economics fields, this book equips practitioners with the necessary techniques to measure and manage risk.

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Numerical Mathematics and Computing 7th Edition, Cheney

Numerical Mathematics and Computing 7th Edition PDF Download Ebook. E. Ward Cheney and David R. Kincaid show students of science and engineering the potential computers have for solving numerical problems and give them ample opportunities to hone their skills in programming and problem solving.

This book also helps students learn about errors that inevitably accompany scientific computations and arms them with methods for detecting, predicting, and controlling these errors. Computer codes and other material are now included on the text website--giving you and your students easy access without tedious typing. Matlab, Mathematica, and Maple computer codes and the ¿Overview of Mathematical Software appendix are all now available online.

Because concrete codes and visual aids are helpful to every reader, the authors have added even more figures and numerical examples throughout the text--ensuring students gain solid understanding before advancing to new topics. Completely updated, the new edition includes new sections and material on such topics as the modified false position method, the conjugate gradient method, Simpsons method, and more.

Citation to recent references reflects the latest developments from the field. Reorganized and revamped, new appendices offer a wealth of supplemental material, including advice on good programming practices, coverage of numbers in different bases, details on IEEE floating-point arithmetic, and discussions of linear algebra concepts and notation.

The first two chapters in the previous edition on Mathematical Preliminaries, Taylor Series, Oating-Point Representation, and Errors have been combined into a single introductory chapter to allow instructors and students to move quickly. Some sections and material have been re-moved from the new edition such as the introductory section on numerical integration. Some material and many bibliographical items have been moved from the textbook to the website.

The two chapters, in the previous edition, on Ordinary Differential Equations have been combined into one chapter. Many of the pseudocodes from the text have been programmed in MATLAB, Mathematica, and Maple and appear in the website so that they are easily accessible. More figures and numerical examples have been added.

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Numerical Recipes: The Art of Scientific Computing 3e

Numerical Recipes: The Art of Scientific Computing 3rd Edition PDF Download Ebook. William H. Press, Saul A. Teukolsky, William T. Vetterling and Brian P. Flannery describe basic mathematics and computer science and proceeds to complete, working routines. Widely recognized as the most comprehensive, accessible and practical basis for scientific computing, this new edition incorporates more than 400 Numerical Recipes routines, many of them new or upgraded.

The executable C++ code, now printed in color for easy reading, adopts an object-oriented style particularly suited to scientific applications. The whole book is presented in the informal, easy-to-read style that made earlier editions so popular. The book includes commented full listings of now more than 400 unique C++ routines that can be downloaded in machine-readable form (see right) for inclusion in users' programs.

This text has 2 new chapters, 25 new sections, and is about 25% longer than the 2nd edition. Its code is wholeheartedly object oriented, demonstrating diverse techniques for using the full power of C++. Color and marginal labels add clarity to the text and code. Journal references now include article titles.

New or expanded topics include classification and inference (including Gaussian mixture models, hidden Markov modeling, hierarchical clustering, support vector machines); computational geometry (including KD trees, quad- and octrees, Delaunay triangulation, polygons, triangles, spheres); many new statistical distributions; completely new ODE routines; expanded random deviates; spectral and pseudospectral methods for PDEs.

Other topics include interior point methods for linear programming; expanded sparse matrices; interpolation in multidimensions; quadrature by variable transformation; fast spherical harmonic transforms; fast incremental quantile estimation; information theoretic properties of distributions; wavelets on the interval; kriging; phylogenetic trees; soft error decoding; stochastic simulation of reaction networks; and much, much more!

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Numerical Analysis 2nd Edition by Timothy Sauer

Numerical Analysis 2nd Edition PDF Download Ebook. Timothy Sauer covers not only the standard topics but also some more advanced numerical methods being used by computational scientists and engineers—topics such as compression, forward and backward error analysis, and iterative methods of solving equations—all while maintaining a level of discussion appropriate for undergraduates.

Each chapter contains a Reality Check, which is an extended exploration of relevant application areas that can launch individual or team projects. MATLAB® is used throughout to demonstrate and implement numerical methods. The Second Edition features many noteworthy improvements based on feedback from users, such as new coverage of Cholesky factorization, GMRES methods, and nonlinear PDEs.

Chapter 0 (optional) provides students with the fundamental building blocks they will need in later chapters. The entire text is designed to move from elementary ideas to more sophisticated concepts to avoid sudden jumps in level.

Spotlights throughout the text highlight the five major ideas of Numerical Analysis. These spotlights comment on the topic at hand and make informal connections to other expressions of the same concept elsewhere in the book helping students connect what they already know to a new concept.

Reality Checks appear throughout the text to provide concrete examples of the way numerical methods lead to solutions of important technological problems showing students how numerical analysis applies to their lives.

Optional MATLAB® expositions are used throughout the text, giving students and instructors the ability to use a common computing language to solve all of the interface problems: data input/output, plotting, etc. in one fell swoop. Appendix B is a short MATLAB tutorial that can be used as a first introduction to students who have not used MATLAB, or as a reference to students already familiar with MATLAB.

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Numerical Analysis 9th Edition, Richard Burden and Faires

Numerical Analysis 9th Edition PDF Download Ebook. Richard L. Burden and J. Douglas Faires offer introduction to the theory and application of modern numerical approximation techniques for students taking a one- or two-semester course in numerical analysis. With an accessible treatment that only requires a calculus prerequisite, Burden and Faires explain how, why, and when approximation techniques can be expected to work, and why, in some situations, they fail.

A wealth of examples and exercises develop students' intuition, and demonstrate the subject's practical applications to important everyday problems in math, computing, engineering, and physical science disciplines. The first book of its kind built from the ground up to serve a diverse undergraduate audience, three decades later Burden and Faires remains the definitive introduction to a vital and practical subject.

Balances theory and methods to stake a wide middle ground between audiences who need to know the mathematics and audiences who only need to know the essential techniques. Flexible coverage to suit one- or two-semester courses and differing student levels, with careful attention paid to marking optional material and alternate paths for instructors. Specific instructions are given for Maple in limited cases where software-specific questions are absolutely required.

Language and software neutral programs in book are supported on companion website by specific program code for Maple, Mathematica, MATLAB, C, FORTRAN, Java, and Pascal to cover all technologies the majority of the market will use. Author website includes mid-cycle updates and additions to this program code to keep up with new software releases.

Virtually every concept in the text is illustrated by example, and this edition contains more than 2000 class-tested exercises ranging from elementary applications of methods and algorithms to generalizations and extensions of the theory. The exercise sets include many applied problems from diverse areas of engineering, as well as from the physical, computer, biological, and social sciences.

The design of the text gives instructors flexibility in choosing topics they wish to cover, selecting the level of theoretical rigor desired, and deciding which applications are most appropriate or interesting for their classes. Theory coverage emphasizes mathematical thought and is especially accessible for students who've optionally taken undergrad math foundations courses like Real Analysis or Transition to Advanced Math.

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