Teaching |
I am
teaching Advanced Signal Processing in January 2014. Here are the details. It
is tentatively a 13 week course with 2 lectures per week. The detailed schedule
is as follows:
Lecture No. |
Contents |
1 |
Some
Fundamentals of Functional Analysis |
2 |
Linear
Inverse Problems and Introduction to Least Squares |
3 |
A Linear
Algebraic Look at Least Squares |
4 |
Regularization
and Applications of Least Squares |
5 |
Solving
Least Squares Problems (Algorithms) |
6 |
Under-determined
Linear Inverse Problems and Compressed Sensing |
7 |
Compressed
Sensing: Applications |
8 |
Compressed
Sensing: Algorithms - greedy methods |
9 |
Compressed
Sensing: Algorithms - optimization based |
10 |
Group-sparsity,
row-sparsity and other variants of Compressed Sensing |
11 |
Low-rank Matrix
Recovery: Theory |
12 |
Low-rank Matrix
Recovery: Applications |
13 |
Low-rank Matrix
Recovery: Algorithms |
14 |
Low-rank Matrix
Recovery: Algorithms (contd.) |
15 |
Combining
Sparsity with Rank Deficiency |
16 |
Student
Paper Presentation |
17 |
Student
Paper Presentation (contd.) |
18 |
ARMA
Parameter Estimation |
19 |
Kalman Filtering |
20 |
MLE and
MAP estimation |
21 |
Markov
Chains |
22 |
Hidden
Markov Model |
23 |
Student
Project Presentation |
24 |
Student
Project Presentation (contd.) |
25 |
Student
Project Presentation (contd.) |
26 |
Student
Project Presentation (contd.) |
Evaluation
20% - Class Tests
20% - Home Assignments
10% - Mid Terms
40% - Final Project
10% - Final Exam