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Due Wednesday November 13, in class

• Section 7.1
  • Read Section 7.1.
  • Maple worksheet on SVD image compression of flags, Maple worksheet on SVD image compression of other images (the Maple code inputs images in tiff format). (Maple worksheet credit: John May (modified by Russell Blyth))
  • Watch Lecture 29: Singular Value Decomposition of the MIT OpenCourseWare series.
  • Worked example (group work): 13*.
    • 13*. Follow the directions for Problem 13 in Problem Set 7.1, with \[A = \left[\matrix{2&0&1\cr 2&1&0}\right].\] Hint: for an \(m\times n\) matrix with \(m < n\), use the result of Problem 3, which reduces the work to be done by considering the SVD of \(A^t\) first.
  • Homework: 1-3, 5, 6, 12-15, 17
  • Hand In: 13**, 15*:
    • 13**. Follow the directions for Problem 13 in Problem Set 7.1, with \[A = \left[\matrix{1&0&2\cr 1&2&0}\right].\] Hint: for an \(m\times n\) matrix with \(m < n\), use the result of Problem 3, which reduces the work to be done by considering the SVD of \(A^t\) first.
    • 15*. Follow the directions for Problem 15 in Problem Set 7.1, with \(A = \left[\matrix{1&4\cr 2&8}\right]\) (compute the correct matrices \(A^tA\) and \(AA^t\)).
• Section 7.2
  • Read Section 7.2.
  • Tim Baumann's SVD image compression demo web page
  • Worked example (group work): 2*.
    • 2*. Follow the directions for Problem 3 in Problem Set 7.2, with \[A_1 = \left[\matrix{2&2&1&1\cr 2&2&1&1\cr 1&1&1&1}\right], \ \mbox{and}\ A_2 = \left[\matrix{1&2&2&2\cr 1&1&1&1\cr 1&3&3&3}\right].\]
  • Homework: 2, 3
  • Hand In: 2**:
    • 2**. Follow the directions for Problem 3 in Problem Set 7.2, with \[A_1 = \left[\matrix{2&2&1&1\cr 1&1&1&1\cr 3&3&2&2}\right], \ \mbox{and}\ A_2 = \left[\matrix{2&2&1&1\cr 3&3&1&1\cr 1&1&1&1}\right].\]