Numerical Methods for Scientific Computing

J. H. Heinbockel

ISBN 10: 1412031532 / ISBN 13: 9781412031530

Published by Trafford Publishing Sep 2007, 2007

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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 materialis 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. 508 pp. Englisch.

Seller Inventory # 9781412031530

Bibliographic Details

• Title: Numerical Methods for Scientific Computing
• Publisher: Trafford Publishing Sep 2007
• Publication Date: 2007
• Language: English
• ISBN 10: 1412031532
• ISBN 13: 9781412031530
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 280W x 210H x 28D millimeters 280 millimeters width by 210 millimeters height by 28 millimeters depth
• Weight: 1229 grams

About this title

Synopsis

Numerical Methods for Scientific Computing is an introducion to numer-
ical 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 approxima-
tion techniques. The chapter five investigates curve fitting using least squares
and linear reqression. The chapter six presents the topics of difference equa-
tions and Z-transforms. The chapter seven concentrates on numerical differ-
entiation and integration methods. Chapter eight examines numerical solu-
tion 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. 507pp.
8
× 10.

About the Author

.
Dr. John H. Heinbockel is Professor Emeritus of
Mathematics and Statistics from Old Dominion University,
Norfolk, Virginia. He received his Ph.D. in applied
mathematics from North Carolina State University in
1964. He joined Old Dominion University in 1967 and
since then has taught a variety of mathematics courses
at both the undergraduate and graduate level. He has
been the principal investigator on many research grants.
During this time he has produced numerous technical
papers in the areas of applied mathematics.