18.335J / 6.337J Introduction to Numerical Methods, Fall 2010
This course offers an advanced introduction to numerical linear algebra. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating point standard, sparse and structured matric...
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| Format: | Learning Object |
| Language: | en-US |
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2019
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| Online Access: | https://hdl.handle.net/1721.1/122006 |
| _version_ | 1826195814437879808 |
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| author | Johnson, Steven G. |
| author2 | Massachusetts Institute of Technology. Department of Mathematics |
| author_facet | Massachusetts Institute of Technology. Department of Mathematics Johnson, Steven G. |
| author_sort | Johnson, Steven G. |
| collection | MIT |
| description | This course offers an advanced introduction to numerical linear algebra. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating point standard, sparse and structured matrices, preconditioning, linear algebra software. Problem sets require some knowledge of MATLAB®. |
| first_indexed | 2024-09-23T10:15:54Z |
| format | Learning Object |
| id | mit-1721.1/122006 |
| institution | Massachusetts Institute of Technology |
| language | en-US |
| last_indexed | 2025-03-10T08:40:44Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | mit-1721.1/1220062025-02-24T14:57:41Z 18.335J / 6.337J Introduction to Numerical Methods, Fall 2010 Introduction to Numerical Methods Johnson, Steven G. Massachusetts Institute of Technology. Department of Mathematics Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science numerical linear algebra linear systems eigenvalue decomposition QR/SVD factorization numerical algorithms IEEE floating point standard sparse matrices structured matrices preconditioning linear algebra software Matlab 270102 This course offers an advanced introduction to numerical linear algebra. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating point standard, sparse and structured matrices, preconditioning, linear algebra software. Problem sets require some knowledge of MATLAB®. 2019-08-20T19:30:37Z 2019-08-20T19:30:37Z 2010-12 2019-08-20T19:30:59Z Learning Object 18.335J-Fall2010 18.335J 6.337J IMSCP-MD5-636c1ffb66552969b65e4be5eeba9381 https://hdl.handle.net/1721.1/122006 en-US http://hdl.handle.net/1721.1/75282 This site (c) Massachusetts Institute of Technology 2019. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. 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| spellingShingle | numerical linear algebra linear systems eigenvalue decomposition QR/SVD factorization numerical algorithms IEEE floating point standard sparse matrices structured matrices preconditioning linear algebra software Matlab 270102 Johnson, Steven G. 18.335J / 6.337J Introduction to Numerical Methods, Fall 2010 |
| title | 18.335J / 6.337J Introduction to Numerical Methods, Fall 2010 |
| title_full | 18.335J / 6.337J Introduction to Numerical Methods, Fall 2010 |
| title_fullStr | 18.335J / 6.337J Introduction to Numerical Methods, Fall 2010 |
| title_full_unstemmed | 18.335J / 6.337J Introduction to Numerical Methods, Fall 2010 |
| title_short | 18.335J / 6.337J Introduction to Numerical Methods, Fall 2010 |
| title_sort | 18 335j 6 337j introduction to numerical methods fall 2010 |
| topic | numerical linear algebra linear systems eigenvalue decomposition QR/SVD factorization numerical algorithms IEEE floating point standard sparse matrices structured matrices preconditioning linear algebra software Matlab 270102 |
| url | https://hdl.handle.net/1721.1/122006 |
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