|
Showing 1 - 2 of
2 matches in All Departments
Designed for a one-semester course, Introduction to Numerical
Analysis and Scientific Computing presents fundamental concepts of
numerical mathematics and explains how to implement and program
numerical methods. The classroom-tested text helps students
understand floating point number representations, particularly
those pertaining to IEEE simple and double-precision standards as
used in scientific computer environments such as MATLAB (R) version
7. Drawing on their years of teaching students in mathematics,
engineering, and the sciences, the authors discuss computer
arithmetic as a source for generating round-off errors and how to
avoid the use of algebraic expression that may lead to loss of
significant figures. They cover nonlinear equations, linear algebra
concepts, the Lagrange interpolation theorem, numerical
differentiation and integration, and ODEs. They also focus on the
implementation of the algorithms using MATLAB (R). Each chapter
ends with a large number of exercises, with answers to odd-numbered
exercises provided at the end of the book. Throughout the seven
chapters, several computer projects are proposed. These test the
students' understanding of both the mathematics of numerical
methods and the art of computer programming.
Teach Your Students Both the Mathematics of Numerical Methods and
the Art of Computer Programming Introduction to Computational
Linear Algebra presents classroom-tested material on computational
linear algebra and its application to numerical solutions of
partial and ordinary differential equations. The book is designed
for senior undergraduate students in mathematics and engineering as
well as first-year graduate students in engineering and
computational science. The text first introduces BLAS operations of
types 1, 2, and 3 adapted to a scientific computer environment,
specifically MATLAB (R). It next covers the basic mathematical
tools needed in numerical linear algebra and discusses classical
material on Gauss decompositions as well as LU and Cholesky's
factorizations of matrices. The text then shows how to solve linear
least squares problems, provides a detailed numerical treatment of
the algebraic eigenvalue problem, and discusses (indirect)
iterative methods to solve a system of linear equations. The final
chapter illustrates how to solve discretized sparse systems of
linear equations. Each chapter ends with exercises and computer
projects.
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.