APMA 1940D - Iterative Methods

Institution:
Brown University
Subject:
Description:
Large, sparse systems of equations arise in many areas of mathematical application and in this course we explore the popular numerical solution techniques being used to efficiently solve these problems. Throughout the course we will study preconditioning strategies, Krylov subspace acceleration methods, and other projection methods. In particular, we will develop a working knowledge of the Conjugate Gradient and Minimum Residual (and Generalized Minimum Residual) algorithms. Multigrid and Domain Decomposition Methods will also be studied as well as parallel implementation, if time permits.
Credits:
1.00
Credit Hours:
Prerequisites:
Corequisites:
Exclusions:
Level:
Instructional Type:
Lecture
Notes:
Additional Information:
Historical Version(s):
Institution Website:
Phone Number:
(401) 863-1000
Regional Accreditation:
New England Association of Schools and Colleges
Calendar System:
Semester

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