Numerical Methods For Scientific Computing

This work addresses the increasingly important role of numerical methods in science and engineering. It combines traditional and well-developed topics with other material such as interval arithmetic, elementary functions, operator series, convergence acceleration, and continued fractions.

This text is intended for a first course in Numerical Analysis taken by students majoring in mathematics, engineering, computer science, and the sciences. This text emphasizes the mathematical ideas behind the methods and the idea of mixing methods for robustness. The optional use of MATLAB is incorporated throughout the text.

This book introduces the main topics of modern numerical analysis: sequence of linear equations, error analysis, least squares, nonlinear systems, symmetric eigenvalue problems, three-term recursions, interpolation and approximation, large systems and numerical integrations. The presentation draws on geometrical intuition wherever appropriate and is supported by a large number of illustrations, exercises, and examples.

BL Ideal numerical methods and programming text for students, lecturers, and professionals alike This book covers the whole range of numerical mathematics. Throughout, the author presents a unified approach to theory, algortithms, applications, and the use of software.

Numerical Methods for Scientific Computing is an introducion to numerical methods and analysis techniques that can be used to solve a variety of complicated engineering and scientific problems. The material is suitable for upper level college undergraduates or beginning graduate students. There is more than enough material for a two semester course in numerical methods and analysis for mathematicians, engineers, physicists, chemistry and science majors. Chapter one reviews necessary background prerequisite material. The chapter two illustrates techniques for finding roots of equations. Chapter three studies solution methods applicable for handling linear and nonlinear systems of equations. Chapter four introduces interpolation and approximation techniques. The chapter five investigates curve fitting using least squares and linear reqression. The chapter six presents the topics of difference equations and Z-transforms. The chapter seven concentrates on numerical differentiation and integration methods. Chapter eight examines numerical solution techniques for solving ordinary differential equations and chapter nine considers numerical solution techniques for solving linear partial differential equations. The chapter ten develops Monte Carlo techniques for simulating and analyzing complex systems. The final chapter eleven presents parallel computing considerations together with selected miscellaneous topics.

Advanced Mathematics

A comprehensive guide to the theory, intuition, and application of numerical methods in linear algebra, analysis, and differential equations. With extensive commentary and code for three essential scientific computing languages: Julia, Python, and Matlab.

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 an