-
-
Courses
Find courses by:
Collections
Cross-Disciplinary Topic Lists
Translated Courses
-
About
-
Donate
-
Featured Sites
 | If A is symmetric and positive definite, there is an orthogonal matrix Q for which A = QΛQT. Here Λ is the matrix of eigenvalues. Singular Value Decomposition lets us write any matrix A as a product UΣVT where U and V are orthogonal and Σ is a diagonal matrix whose non-zero entries are square roots of the eigenvalues of ATA. The columns of U and V give bases for the four fundamental subspaces. |
Work the problems on your own and check your answers when you're done.
MIT OpenCourseWare makes the materials used in the teaching of almost all of MIT's subjects available on the Web, free of charge. With more than 2,000 courses available, OCW is delivering on the promise of open sharing of knowledge.
© 2001–2012
Massachusetts Institute of Technology
Your use of the MIT OpenCourseWare site and materials is subject to our Creative Commons License and other terms of use.
