Lecture 29: Singular value decomposition

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The singular value decomposition of a matrix is usually referred to as the SVD. This is the final and best factorization of a matrix. The factors are orthogonal matrix, diagonal matrix, orthogonal matrix. Any matrix whatsoever has this singular value decomposition. One thing we bring together in this lecture is the very good family of matrices that we just studied: symmetric, positive, definite.

These video lectures of Professor Gilbert Strang teaching 18.06 were recorded in Fall 1999 and do not correspond precisely to the current edition of the textbook. However, this book is still the best reference for more information on the topics covered in each lecture.

Strang, Gilbert. Introduction to Linear Algebra. 5th ed. Wellesley-Cambridge Press, 2016. ISBN: 9780980232776.

Instructor/speaker: Prof. Gilbert Strang

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