- Exam 2 due NOVEMBER 19 BY THE BEGINNING OF CLASS
- First
homework assignment , due end of class, Sept. 12.
- Solutions to first homework assignment.
- Second
homework assignment , due end of class, Sept. 19.
- Solutions to second homework assignment. *NOTE THE ALGORITHM in number 7 the definition of a(i) in part 2 should have a A(index1:index2,i), not
A(index1:index2,:) in it.
- Third
homework assignment , due end of class, Sept. 26.
- Solutions to third homework assignment.
- Fourth
homework assignment , due end of class, Oct. 17.
- ans key
to assignment 4.
- Fifth
homework assignment , due end of class, Oct. 24.
- Solutions
to fifth
homework assignment (except I used the wrong matrix for problem 4 - will correct this!)
- Sixth
homework assignment , due end of class, Oct. 31.
- Solutions to 6th assignment
- Seventh
homework assignment , due end of class, Nov. 6
- Ans. to 7th homework assignment
- First set of lecture notes covering intro/background, book chapters 1-3. Note the
first set of notes is over more than one class lecture!
- Second set of lecture notes covering book chapter 4-5.
- Third set of lecture notes covering book chapter projectors (chapt. 6).
- Fourth set of lecture notes covering QR decomposition via GS (With Revisions! Oct. 2).
- Fifth set of lecture notes : compare MGS and CGS, Householder reflectors
- Sixth set of lecture notes : Least squares, conditioning and stability
- Seventh set of lecture notes : floating point arith., conditioning, stability
- Eigth set of lecture notes : Gaussian elimination, Cholesky decomposition
- Set 9 of lecture notes : Eigenvalues, eigenvectors, eigencomputation part 1 (need
to change last term in char. poly example to z^2
- Set 10 of lecture notes : Eigenvalues, eigenvectors, eigencomputation part 2
- Eleventh of lecture notes : Eigencomputation part 3 (updated Nov. 7)
- Set 12 of lecture notes : applications/examples for eigen-information
- Set 13 of lecture notes : SVD computation
In-class pca demo based on the web tutorial
dst.m
, for hw2
bisection.m algorithm for helping to find eigenvalues of a symmetric tridiagonal matrix, user must provide the shift(s).