Engineering Sciences 106 - Numerical Linear Algebra

Institution:

Dartmouth College

Subject:

Description:

Not offered in the period from 08F through 10S The course examines in the context of modern computational practice algorithms for solving linear systems Ax = b and Az = x. Matrix decomposition algorithms, matrix inversion, and eigenvector expansions are studied. Algorithms for special matrix classes are featured, including symmetric positive definite matrices, banded matrices, and sparse matrices. Error analysis and complexity analysis of the algorithms are covered. The algorithms are implemented for selected examples chosen from elimination methods (linear systems), least squares (filters), linear programming, incidence matrices (networks and graphs), diagonalization (convolution), sparse matrices (partial differential equations). Prerequisite: Computer Science 26, Mathematics 26, or Engineering Sciences 91. Students are to be familiar with approximation theory, error analysis, direct and iterative technique for solving linear systems, and discretization of continuous problems to the level normally encountered in an undergraduate course in numerical analysis. Zomordian.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.dartmouth.edu

Phone Number:

(603) 646-1110

Regional Accreditation:

New England Association of Schools and Colleges

Calendar System:

Quarter

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