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A homework assignment for a math 477 course, which covers singular value decomposition (svd). The assignment includes problems on determining svds of various matrices, finding the minimum and maximum singular values of a matrix, and finding the orthogonal projector onto the range of a matrix. The assignment also includes a proof and a geometric interpretation of a statement about orthogonal projectors and unitary matrices.
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(a)
, (b)
, (c)
(^) , (d)
, (e)
A =
is approximately 1.6180. Using the SVD, work out (the “by-hand” method is from now on allowed) the exact values of σmin(A) and σmax(A) for this matrix.
A =
Answer the following questions by hand calculation.
(a) What us the orthogonal projector P onto range(A), and what is the image under P of the vector [1, 2 , 3]∗? (b) Same questions for B.