ELL 705, II semester 201617
This is the the webpage for ELL 705, II semester 201617
Stochastic Filtering and Identification
Instructor
Shaunak Sen
Email: shaunak.sen@ee.iitd.ac.in
Lectures: MTuF 12:0012:50pm
Room: IIA201
Announcements
28.04.2017: MAJOR TEST scheduled from 3:30PM5:30PM on Sat, 05.05.2015 in LH621. Please check Exam Schedule for uptodate information.
17.04.2017: MINOR TEST 2 solutions posted.
22.03.2017: MINOR TEST 2 scheduled from 11AM12PM on Sat, 25.03.2017 in LH623. Please check Exam Schedule for uptodate information.
06.03.2017: HW2 and Project information posted.
20.02.2017: MINOR TEST 1 solutions posted.
30.01.2017: MINOR TEST 1 scheduled from 23PM on Fri, 03.02.2017 in LH623. Please check Exam Schedule for uptodate information.
24.01.2017: HW1 posted.
14.01.2017: Webpage online.
Lectures
S. No.  Date  Topic  Advised Reading  Homework 
1  Week 1 (Jan 3)  Introduction  Ljung 1.4  
2  Week 2 (Jan 10, 13)  Example (LeastSquares) Mean and Variance of Estimate  Lecture Ljung 1.3  
3  Week 3 (Jan 16, 17, 20)  Example (Kalman Filter) Models Linear DiscreteTime Models (ARX, ARMA, ARMAX, BoxJenkins) Predictors Others – StateSpace, Linear TimeVarying, Nonlinear Methods LeastSquares  Ljung 4.14.2 Ljung 3.13.2 Ljung 4.3, 5.15.3 Lecture  
4  Week 4 (Jan 23, 24, 27)  LeastSquares Discussion  Ljung Appendix II, 7.4 Lecture, Lecture  HW1 
5  Week 5 (Jan 30, Feb 3)  LeastSquares MINOR TEST 1  Lecture  
6  Week 6 (Feb 6, 7, 10)  PseudoLinear Regression InstrumentVariable Methods Maximum Likelihood  Lecture, Code Ljung 7.6 Lecture, Code Ljung 7.4, Lecture  
7  Week 7 (Feb 13, 14)  CramerRao Bound Recursive LeastSquares  Ljung Appendix 7A, Lecture Ljung 11.111.5, Lecture  
8  Week 8 (Feb 20, 21, 22)  TimeVarying Parameters Convergence  Lecture Lecture Lecture, Ljung 8.18.4, 9.19.3, Code  
9  Week 9 (MidSemester Break)    
10  Week 10 (Mar 6, 7, 10)  Extended Kalman Filter Define Parameter as State Linearization  Anderson & Moore 1, 8.18.2 Lecture, Lecture, Lecture  HW2 Project 
11  Week 11 (Mar 14, 17)  Conditional Probability Moment Generating Functions  Anderson & Moore 2.3 Lecture, Lecture  
12  Week 12 (Mar 20, 21, 25  Minor Test 2)  Minimum Variance Estimate HW2 discussion  Anderson & Moore 2.3 Lecture, Lecture  
13  Week 13 (Mar 27, 28, 31)  Discretetime Kalman Filtering Problem and Solution  Anderson & Moore 3.1 Lecture, Lecture, Lecture  
14  Week 14 (Apr 1, 3, 7)  Proof  Anderson & Moore 3.1  
15  Week 15 (Apr 11)  Properties  BLUE, TimeInvariance, Stability  Anderson & Moore 3.2, 4 Lecture  
16  Week 16 (Apr 17, 18, 21)  Linear Minimum Variance Estimator Innovation Sequence  Anderson & Moore 5 Lecture, Lecture  
17  Week 17 (Apr 25, 27, 28)  Projects 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, PrenticeHall, 1989.
B. D. O. Anderson and J. B. Moore, Optimal Filtering (Dover Books on Electrical Engineering).
