AMSC 460 Computational Methods
Spring 2011
Course Description:
Basic computational methods for interpolation, least squares, approximation, numerical quadrature, numerical solution of nonlinear equations, systems of linear equations, and initial value problems for ordinary differential equations. Emphasis on the methods and their computational properties rather on their analytic aspects.
Prerequisite/Corequisite and Credits:
 MATH 240 and 241, CMSC 105 or CMSC 106 or CMSC 114 or ENEE 114. Homework assignment will include exercises using MATLAB; Familiarity with and accessibility to MATLAB are expected.
Textbook:
 Required: Introduction to Scientific Computing (2nd Edition) by C.F. van Loan [ISBN 0139491570] Suggested: Numerical Computing with Matlab by Cleve B. Moler [online text available]
MATLAB Resources:
 Access to MATLAB: Individual students are responsible for gaining the access to MATLAB Using the univeristy computes that already have MATLAB Student Edition of MATLAB available from UMD OIT Users guides Tutorial at University of Maryland. Introduction at University of Maryland. Many other resources are available online. Demo codes Basic plotting [Feb 15]
Instructor: Kayo Ide
 Email: ide at umd.edu Office at CSCAMM: CSIC 4127 at AOSC: CSS  3403
 Email: anorwood at math.umd.edu [contact by email for appointment]
Schedule:
Weekly
 9:30am-10:45am TuTh [CSIC 2118] Class 2:00pm- 3:00pm Tu [CSS 3403] Office hour 3:00pm- 4:00pm W [CSIC 4127] Office hour
Extra
 11:00am-12:30am, May 9 Mon [CSS 3403] Office hour
Exams
 March 31, in class Th Mid Term May 13, 8:00am-10:00am F Final
Outline of the Course:
Topics to be Covered
 Introduction, Computer Arithmetic, and Errors Course Overview Floating Point Representation Approximation and Error Analysis Interpolation and Approximation of Functions Polynomical Interpolation Piecewise Polynomial Interpolation Spline Interpolation Integration Simple Rules Adaptive Rules Matrix Computation Solution of Linear Equations Gaussian Elimination Pivoting and Conditioning Sparse Systems Least Squares Solution of Nonlinear Equations and Optimization Rootfinding and Minimization of Scalar Functions Minimization of Multivariate Functions Solution of Ordinary Differential Equations One- and Multi-step Methods Stiff Systems