Books about Numerical from Amazon.com

Master MATLAB(r)!

If you want a clear, easy-to-use introduction to MATLAB(r), this book is for you! The Third Edition of Amos Gilat's popular MATLAB(r), An Introduction with Applications requires no previous knowledge of MATLAB and computer programming as it helps you understand and apply this incredibly useful and powerful mathematical tool.

Thoroughly updated to match MATLAB(r)'s newest release, MATLAB(r) 7.3 (R2007b), the text takes you step by step through MATLAB(r)'s basic features--from simple arithmetic operations with scalars, to creating and using arrays, to three-dimensional plots and solving differential equations. You'll appreciate the many features that make it easy to grasp the material and become proficient in using MATLAB(r), including:
* Sample and homework problems that help you hands-on practice solving the kinds of problems you'll encounter in future science and engineering courses
* New coverage of the Workspace Window and the save and load commands, Anonymous Functions, Function Functions, Function Handles, Subfunctions and Nested Functions
* In-depth discussions of script files, 2-D and 3-D plotting, function files, programming (flow control), polynomials, curve fitting, interpolation, and applications in numerical analysis

By showing you not just how MATLAB(r) works but how to use it with real-world applications in mathematics, science, and engineering, MATLAB(r), An Introduction with Applications, Third Edition will turn you into a MATLAB(r) master faster than you imagined..
Price: $54.19 [Notify me when price goes down.]

Co-authored by four leading scientists from academia and industry, Numerical Recipes Third Edition starts with 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. Please visit www.nr.com or www.cambridge.org/us/numericalrecipes for more details. New key features:

• 2 new chapters, 25 new sections, 25% longer than Second Edition
• Thorough upgrades throughout the text
• Over 100 completely new routines and upgrades of many more.
• New Classification and Inference chapter, including Gaussian mixture models, HMMs, hierarchical clustering, Support Vector Machines
• New Computational Geometry chapter covers KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres
• New sections include interior point methods for linear programming, Monte Carlo Markov Chains, spectral and pseudospectral methods for PDEs, and many new statistical distributions
• An expanded treatment of ODEs with completely new routines

Plus comprehensive coverage of

• linear algebra, interpolation, special functions, random numbers, nonlinear sets of equations, optimization, eigensystems, Fourier methods and wavelets, statistical tests, ODEs and PDEs, integral equations, and inverse theory

And much, much more! Visit the authors' web site for information about electronic subscriptions www.nr.com/aboutNR3book.html.
Price: $53.00 [Notify me when price goes down.]

There has been a dramatic growth in the development and application of Bayesian inferential methods Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticians in education and industry.

Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. The early chapters present the basic tenets of Bayesian thinking by use of familiar one and two-parameter inferential problems. Bayesian computational methods such as Laplace's method, rejection sampling, and the SIR algorithm are illustrated in the context of a random effects model. The construction and implementation of Markov Chain Monte Carlo (MCMC) methods is introduced. These simulation-based algorithms are implemented for a variety of Bayesian applications such as normal and binary response regression, hierarchical modeling, order-restricted inference, and robust modeling. Algorithms written in R are used to develop Bayesian tests and assess Bayesian models by use of the posterior predictive distribution. The use of R to interface with WinBUGS, a popular MCMC computing language, is described with several illustrative examples.

This book is a suitable companion book for an introductory course on Bayesian methods. Also the book is valuable to the statistical practitioner who wishes to learn more about the R language and Bayesian methodology. The LearnBayes package, written by the author and available from the CRAN website, contains all of the R functions described in the book.

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Price: $39.04 [Notify me when price goes down.]

Solutions-based approach to quick calculations in structural element design and analysis

Now updated with 30% new material, Roark Formulas for Stress and Strain, Seventh Edition, is the ultimate resource for designers, engineers, and analysts who need to calculate loads and stress. This landmark reference from Warren Young and Richard Budynas provides you with equations and diagrams of structural properties in an easy-to-use, thumb-through format. Updated, with a user-friendly page layout, this new edition includes expanded coverage of joints, bearing and shear stress, experimental stress analysis, and stress concentrations, as well as material behavior coverage and stress and strain measurement. You’ll also find expanded tables and cases; improved notations and figures in the tables; consistent table and equation numbering; and verification of correction factors..
Price: $71.44 [Notify me when price goes down.]

This is a concise, insightful introduction to the field of numerical linear algebra The clarity and eloquence of the presentation make it popular with teachers and students alike. The text aims to expand the reader's view of the field and to present standard material in a novel way. All of the most important topics in the field are covered with a fresh perspective, including iterative methods for systems of equations and eigenvalue problems and the underlying principles of conditioning and stability. Presentation is in the form of 40 lectures, which each focus on one or two central ideas. The unity between topics is emphasized throughout, with no risk of getting lost in details and technicalities. The book breaks with tradition by beginning with the QR factorization - an important and fresh idea for students, and the thread that connects most of the algorithms of numerical linear algebra.

Contents: Preface; Acknowledgments; Part I: Fundamentals. Lecture 1: Matrix-Vector Multiplication; Lecture 2: Orthogonal Vectors and Matrices; Lecture 3: Norms; Lecture 4: The Singular Value Decomposition; Lecture 5: More on the SVD; Part II: QR Factorization and Least Squares. Lecture 6: Projectors; Lecture 7: QR Factorization; Lecture 8: Gram-Schmidt Orthogonalization; Lecture 9: MATLAB; Lecture 10: Householder Triangularization; Lecture 11: Least Squares Problems; Part III: Conditioning and Stability. Lecture 12: Conditioning and Condition Numbers; Lecture 13: Floating Point Arithmetic; Lecture 14: Stability; Lecture 15: More on Stability; Lecture 16: Stability of Householder Triangularization; Lecture 17: Stability of Back Substitution; Lecture 18: Conditioning of Least Squares Problems; Lecture 19: Stability of Least Squares Algorithms; Part IV: Systems of Equations. Lecture 20: Gaussian Elimination; Lecture 21: Pivoting; Lecture 22: Stability of Gaussian Elimination; Lecture 23: Cholesky Factorization; Part V: Eigenvalues. Lecture 24: Eigenvalue Problems; Lecture 25: Overview of Eigenvalue Algorithms; Lecture 26: Reduction to Hessenberg or Tridiagonal Form; Lecture 27: Rayleigh Quotient, Inverse Iteration; Lecture 28: QR Algorithm without Shifts; Lecture 29: QR Algorithm with Shifts; Lecture 30: Other Eigenvalue Algorithms; Lecture 31: Computing the SVD; Part VI: Iterative Methods. Lecture 32: Overview of Iterative Methods; Lecture 33: The Arnoldi Iteration; Lecture 34: How Arnoldi Locates Eigenvalues; Lecture 35: GMRES; Lecture 36: The Lanczos Iteration; Lecture 37: From Lanczos to Gauss Quadrature; Lecture 38: Conjugate Gradients; Lecture 39: Biorthogonalization Methods; Lecture 40: Preconditioning; Appendix: The Definition of Numerical Analysis; Notes; Bibliography; Index.

Audience: Written on the graduate or advanced undergraduate level, this book can be used widely for teaching. Professors looking for an elegant presentation of the topic will find it an excellent teaching tool for a one-semester graduate or advanced undergraduate course. A major contribution to the applied mathematics literature, most researchers in the field will consider it a necessary addition to their personal collections..
Price: $57.50 [Notify me when price goes down.]

Probablistic models are becoming increasingly important in analyzing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analyzing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it is accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time presents the state of the art in this new and important field..
Price: $30.00 [Notify me when price goes down.]

Co-authored by four leading scientists from academia and industry, Numerical Recipes Third Edition starts with 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. Please visit www.nr.com or www.cambridge.org/us/numericalrecipes for more details. More information concerning licenses is available at: www.nr.com/licenses New key features:

• 2 new chapters, 25 new sections, 25% longer than Second Edition
• Thorough upgrades throughout the text
• Over 100 completely new routines and upgrades of many more.
• New Classification and Inference chapter, including Gaussian mixture models, HMMs, hierarchical clustering, Support Vector Machines
• New Computational Geometry chapter covers KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres
• New sections include interior point methods for linear programming, Monte Carlo Markov Chains, spectral and pseudospectral methods for PDEs, and many new statistical distributions
• An expanded treatment of ODEs with completely new routines

Plus comprehensive coverage of

• linear algebra, interpolation, special functions, random numbers, nonlinear sets of equations, optimization, eigensystems, Fourier methods and wavelets, statistical tests, ODEs and PDEs, integral equations, and inverse theory

And much, much more! This book/CD bundle of the greatly expanded third edition of Numerical Recipes now has wider coverage than ever before, many new, expanded and updated sections, and two completely new chapters. Visit the authors' web site for information about electronic subscriptions www.nr.com/aboutNR3book.html.
Price: $72.70 [Notify me when price goes down.]

Over its first two editions, this best-selling book has become the de facto standard for training and reference material at all levels of CNC programming. Used in hundreds of educational institutions around the world as the primary text for CNC courses, and used daily by many in-field CNC programmers and machine operators, this book literally defines CNC programming. Written with careful attention to detail, there are no compromises. Many of the changes in this new Third Edition are the direct result of comments and suggestions received from many CNC professionals in the field. This extraordinarily comprehensive work continues to be packed with over one thousand illustrations, tables, formulas, tips, shortcuts, and practical examples.

The enclosed CD-ROM now contains a fully functional 15-day shareware version of CNC tool path editor/simulator, NCPlotâ„¢. This powerful, easy-to-learn software includes an amazing array of features, many not found in competitive products. NCPlot offers an unmatched combination of simplicity of use and richness of features. Support for many advanced control options is standard, including a macro interpreter that simulates Fanuc and similar macro programs.

The CD-ROM also offers many training exercises based on individual chapters, along with solutions and detailed explanations. Special programming and machining examples are provided as well, in form of complete machine files, useful as actual programming resources. Virtually all files use Adobe PDF format and are set to high resolution printing.

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Price: $54.44 [Notify me when price goes down.]