ELL 705, II semester 2015-16
This is the the webpage for ELL 705, II semester 2015-16
Stochastic Filtering and Identification
Instructor
Shaunak Sen
E-mail: shaunak.sen@ee.iitd.ac.in
Lectures: MW 11:00-11:50am, Th 12:00-12:50pm
Room: LH605
Announcements
28.04.2016: MAJOR TEST scheduled from 3:30PM-5:30PM on Thu, 05.05.2015 in LH615. Please check Exam Schedule for up-to-date information.
28.04.2016: HW3 posted.
05.04.2016: MINOR TEST 2 solutions posted.
17.03.2016: MINOR TEST 2 scheduled from 4-5PM on Tue, 22.03.2016 in LH615. Please check Exam Schedule for up-to-date information.
25.02.2016: HW2 posted.
25.02.2016: MINOR TEST 1 solutions posted.
08.02.2016: MINOR TEST 1 scheduled from 4-5PM on Sat, 13.02.2016 in LH615. Please check Exam Schedule for up-to-date information.
01.02.2016: HW1 posted.
07.01.2016: Webpage online.
Lectures
| S. No. | Date | Topic | Advised Reading | Homework |
| 1 | Week 1
(Jan 7) | Introduction
Applications
Data, Model, Method | Ljung 1.4 | |
| 2 | Week 2
(Jan 11, 13) | Example (ARX) | Lecture
Ljung 1.3 | |
| 3 | Week 3
(Jan 18, 20, 21) | Mean and Variance of Estimate
Overview | Lecture | |
| 4 | Week 4
(Jan 25, 27, 28) | Models
Linear Discrete-Time Models
(ARX, ARMA, ARMAX, Box-Jenkins, OE)
Predictors
Others – State-Space, Linear Time-Varying, Nonlinear
Methods
Least-Squares |
Lecture
Ljung 4.1-4.2
Ljung 3.1-3.2
Ljung 4.3, 5.1-5.3
Lecture
Ljung Appendix II, 7.3 | |
| 5 | Week 5
(Feb 1, 3, 4) | Maximum Likelihood | Lecture
Ljung Appendix II, 7.4 | HW1 |
| 6 | Week 6
(Feb 8) | Cramer-Rao Bound | | |
| 7 | Week 7
(Feb 15, 17, 18) | Recursive Least-Squares
Time-Varying Parameters
Recursive Maximum Likelihood | Lecture
Lecture
Lecture
Ljung 11.1-11.2,11.4-11.5 | |
| 8 | Week 8
(Feb 22, 24, 25) | Example: ARMAX
Instrument-Variable Methods | Lecture
Example Code
Ljung Example 11.1
Ljung 7.6, 11.3 | HW2 |
| 9 | Week 9
(Mid-Semester Break) | | | |
| 10 | Week 10 | | | |
| 11 | Week 11
(Mar 14, 16, 17) | Convergence
Projects | Lecture
Handout
Example Code | |
| 12 | Week 12
(Mar 22 - Minor Test 2) | | | |
| 13 | Week 13
(Mar 28, 30) | Extended Kalman Filter | Lecture | HW3 |
| 14 | Week 14
(Apr 4, 6, 7) | Kalman Filter (Predicted State) | | |
| 15 | Week 15
(Apr 11, 13, 16) | Parameter as State
Linearization about Last Estimate
Projects | | |
| 16 | Week 16
(Apr 18, 21) | Kalman Filter (Filtered State) | | |
| 17 | Week 17
(Apr 25, 27, 28, 30) | Particle Filter
Overview | |
|
Reference Textbooks
L. Ljung, System Identification: Theory for the User, Prentice Hall, 2nd edition, 1999.
T. Soderstrom and P. Stoica, System Identification, Prentice-Hall, 1989.
Papoulis & Pillai, Probability, Random Variables and Stochastic Processes, McGraw-Hill, 2002.
B. D. O. Anderson and J. B. Moore, Optimal Filtering (Dover Books on Electrical Engineering).
M. S. Grewal and A. P. Andrews, Kalman Filtering: Theory and Practise Using MATLAB.
R. Johansson, System Modelling and Identification.
|