http:^^www.cs.dartmouth.edu^courseguide^grad^cs_106.html

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Date: Wed, 20 Nov 1996 22:11:30 GMTServer: NCSA/1.4.2Content-type: text/htmlLast-modified: Tue, 03 Sep 1996 13:09:45 GMTContent-length: 1477<HTML><HEAD><TITLE>Numerical Linear Algebra</TITLE></HEAD><BODY><H2>Numerical Linear Algebra</H2><H4>(Computer Science 106)</H4><EM>Identical to Engineering Sciences 104</EM><P><B>Times:</B> 98S: Arrange <BR><B>Prerequisite:</B>  <!WA0><A HREF="http://www.cs.dartmouth.edu/courseguide/undergrad/cs_26.html">Computer Science 26</A>, Mathematics 26, or Engineering Science 69. Students are to be familiarwith approximation theory, error analysis, direct and iterative techniques for solving linear systems, anddiscretization of continuous problems to the level normally encountered in an undergraduate course innumerical analysis. <P>The course examines in the context of modern computational practice algorithms for solving linear systems<CODE>Ax = b</CODE> and <CODE>Az = lx</CODE>. Matrix decomposition algorithms, matrix inversion, and eigenvector expansions arestudied. Algorithms for special matrix classes are featured, including symmetric positive definitematrices, banded matrices, and sparse matrices. Error analysis and complexity analysis of the algorithmsare 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). <P><H4><HR><!WA1><IMG ALIGN="middle" SRC="http://www.cs.dartmouth.edu/images/Dtree.gif" WIDTH=34 HEIGHT=39> <!WA2><A HREF="http://www.cs.dartmouth.edu/courseguide/grad//">Back to Dartmouth CS Home Page</A></H4></BODY></HTML>

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