Lectures and Homework 642:550, Summer 2004



The exercises listed here should be prepared for the second class following the one in which they are assigned. Problems will be listed here shortly before they are announced in class. A table of assigned problems will evolve in this space.

Date Section Pages Problems
Jun 28 3.6 205 - 207 14 (both parts from text and extra part from S1, see note).
S1 7 A (see note).
Jun 29 4.2 218 - 221 6, 11 (see note).
4.3 228 - 230 4.
4.Review 241 - 242 13.
S2 4 A.
Jul 01 4.4 238 - 240 1, 12.
S3 3 A, B (see note).
5.1 251 - 253 12, 16 (see note).
Jul 05 5.2 260 - 261 7.
5.3 272 - 274 8
S4 2, 5 and 6 1, 2, and 3.
Jul 06 S5 9 1, 2, 3.
Jul 08 S6 6 1, 2, 3, 4.
Jul 12 5.5 301 - 303 6, 7, 11, 19.
5.Review 319 - 321 15.
Jul 13 S7 4 1, 2, 3.
Jul 15 S8 8 - 9 1, 2, 3, 4.
Jul 19 6.2 337 - 338 2, 7, 11.
Jul 20 6.3 345 - 346 1, 2, 11 (see note).
6.4 352 - 354 11 (see note).
Jul 22 Appendix A 451 - 452 2, 4, 5.
Jul 26 3.3 162 - 165 13.
3.4 180 - 182 15.
3R 208 - 210 33.
no more homework!

Notes

3.6.14
The desired factorization is the reduced factorization described in item 2 on page 197. More details and an extra part are in Supplement 1, section 3 (p.4). There is a misprint in the textbook: the number of columns of L that must be dropped is m-r (matching the rows of U that are discarded), not n-r (as written in the text). [This was noticed by a student in Summer 2003].
S1.A
Part (a) should be an easy calculation, but part (b) may be tedious. It is included to show that the intersection of the subspaces does not depend on the order in which the spaces are written, but the effort involved in a solutions depends on how the problem is formulated.
4.2.11
One part asks to use properties of the determinant to show that the determinant of  every 3 by 3 skew-symmetric matrix is zero.  Another part asks for one example of a 4 by 4 skew-symmetric matrix with nonzero determinant.  This example should be a numerical matrix, and you should find the determinant to be sure that it isn't zero.
S3. A and B
There are some errors in the statements of the problems, but they should have no effect on the solution. Specifically, the determinants give the squares of the measures of the figures, and the measure should be called "area" in A.
5.1.16
The problem statement includes a reference to 4.3.10. That problem suggests some direct ways to evaluate this determinant. None of those methods need be submitted with the solution to 5.1.16, but you are free to use them to check your answer. The point of the exercise if that the use of eigenvalues often leads to a much simpler evaluation of the determinant although it uses deeper theory. A later supplement will say more.
6.3.11
This is based on the generalized eigenvalue problem discussed on pages 343 and 344. It is tempting to solve this problem as described in the footnote on page 344, and the ease with which that succeeds in this case reinforces that instinct. However, a complete solution should use a factorization of M as a product of a matrix and its transpose. Three such factorizations have been described (see page 334), and you should consider all three before using one to find the generalized eigenvalues and their eigenvectors.
6.4.11
This problem uses a simple form of Remark 2 on page 352.

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