Afternotes on Numerical Analysis is the result of the author writing down his notes immediately a...

Combines nonlinear optimization, mathematical control theory, and numerical solution of ordinary ...

Asymptotic methods are frequently used in many branches of both pure and applied mathematics, and...

Provides a rapid introduction to the world of vector and parallel processing for these linear alg...

LAPACK is a library of numerical linear algebra subroutines designed for high performance on work...

The tools to use for problems where the modeling, optimization, or control variable is the struct...

The most comprehensive, up to date account of the popular numerical methods for solving boundary ...

The author uses mathematical techniques to give an in-depth look at models for mechanical vibrati...

Topics emphasized in this book include nonparametric density estimation, multi-dimensional data a...

The subject of mathematical writing has been infused with life once again by Nick Higham as he fo...

Developments in optimization theory, including emphasis on large problems and on interior-point m...

Focuses on the use of iterative methods for solving large sparse systems of linear equations. Tem...

Here is a brief, and easy-to-follow introduction and overview of robust statistics. Peter Huber f...

This title presents an introduction to the classical treatment of Backlund and general surface tr...

This monograph provides a framework for students and practitioners who are working on the solutio...

How do you select a winner from a field of candidates? How do you rank a field of candidates? How...

The Lanczos and conjugate gradient (CG) algorithms are fascinating numerical algorithms. This boo...

This book provides a unified and accessible introduction to the basic theory of finite difference...

Proceedings of the Eighteenth Annual Acm-Siam Symposium on Discrete Algorithms

Learning through doing is the foundation of this book, which allows readers to explore case studi...

This book serves well as an introduction into the more theoretical aspects of the use of spline m...

This book offers an introductory and intermediate-level treatment of all the essential ingredient...

Smart Material Systems describes several novel applications currently under investigation that ex...

This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experi...

A study of the art and science of solving elliptic problems numerically, with an emphasis on prob...

This is the first comprehensive book on the AIMD algorithm, the most widely used method for alloc...

The goal of this textbook is to introduce students to the stochastic analysis tools that play an ...

This classic textbook provides a modern and complete guide to the calculation of eigenvalues of m...

Physics and Partial Differential Equations, Volume II proceeds directly from Volume I (SIAM, 2012...

In this much-expanded second edition, author Yair Shapira presents new applications and a substan...

This classic book provides a rigorous treatment of the Riesz–Fredholm theory of compact operators...

This textbook develops the use of probability and statistics in engineering reliability and maint...

An accessible text for the study of numerical methods for solving least squares problems remains ...

This book introduces finite difference methods for both ordinary differential equations (ODEs) an...

This book describes state-of-the-art advances and applications of the unified transform and its r...

Diffusion has been used extensively in many scientific disciplines to model a wide variety of phe...

Like a pianist who practices from a book of études, readers of Programming Projects in C for Stud...

Riemann–Hilbert problems are fundamental objects of study within complex analysis. Many problems ...

This textbook provides undergraduate students with an introduction to optimization and its uses f...

Mathematical Models in Biology is an introductory book for readers interested in biological appli...

Exact and Approximate Modeling of Linear Systems: A Behavioral Approach elegantly introduces the ...

A comprehensive treatment of optimization problems involving uncertain parameters for which stoch...

This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as the...

The linear sampling method is the oldest and most developed of the qualitative methods in inverse...

Provides an introduction to the state of the art of the probability theory that is most directly ...

Shows both the shortcomings and benefits of each technique, and even demonstrates useful combinat...

Topics include: ways modern statistical procedures can yield estimates of pi more precisely than ...

Included in this volume are the Invited Talks given at the 5th International Congress of Industri...