Lectures and Homework 642:550, Summer 2002



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 24 3.6 205 - 207 14 (both parts).(see note)
3.Review 208 - 210 28.
S1 3 A.
Jun 25 4.2 218 - 221 6, 11 (see note), 16.
4.3 228 - 230 4.
4.Review 241 - 242 3, 13.
Jun 27 4.4 238 - 240 1.
4.Review 241 - 242 20, 23.
5.1 251 - 253 5, 16.
Jul 01 S4 3 1, 2.
5.2 260 - 261 2, 3 (see note), 7.
5.3 272 - 274 8
Jul 02 5.4 286 - 289 1, 6, 12.
5.Review 319 - 321 1, 6, 10.
Jul 08 5.5 301 - 303 6, 7.
5.Review 319 - 321 15.
S6 7 - 8 1, 2, 3, 4.
Jul 09 5.6 315 - 318 16.
S7 4 1, 2, 3.
Jul 11 6.1 328 - 329 12.
6.2 337 - 338 2, 7.
Jul 15 6.3 345 - 346 1, 2, 5 (see note).
Jul 16 6.4 352 - 354 6, 11 (see note).
Appendix A 451 - 452 2, 4.
Jul 18 S8 6 1, 2, 3, 4.
Jul 22 7.2 369 4, 10 (see note).
Jul 23 7.3 378 - 379 1, 5.
7.4 386 - 387 5 (see note).

Notes

3.6.14
The desired factorization is the reduced factorization described in item 2 on page 197.
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.
5.2.3
The two diagonalizing matrices should be essentially different. The rescaling mentioned in Remark 2, and permutation of columns of S, which should have been mentioned there, are always available. Since the matrix A of this problem is diagonalizable in spite of having a repeated eigenvalue, additional diagonalizing matrices are available. At least one column of your second S should not be a multiple of any column of your first choice of S.
6.3.5
This problem mentions a matrix A that is never identified. As part of your solution, find A and show that it is positive definite. In addition, find the pivots of A-4I. What does this tell you about the eigenvalues of A?
6.4.11
This problem uses a simple form of Remark 2 on page 352.
7.2.10
Note that the Euclidean norm that was featured in most of the discussion is not used in this problem. What does it mean for a vector to be of norm 1 in this sense? How does that bound the same norm of the image under the matrix A? (This norm was briefly mentioned in connection with the Perron-Frobenius Theorem.)
7.4.5
Matrix A was introduced in problem 4 and Gershgorin's theorem is stated on page 386, just before that problem.

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