Calendar

LEC # TOPICS KEY DATES
1 Review of Linear Systems, Review of Stochastic Processes, Defining a General Framework

2 Review of Linear Systems, Review of Stochastic Processes, Defining a General Framework (cont.)

3 Introductory Examples for System Identification Problem set 1 out
4 Introductory Examples for System Identification (cont.)

5 Nonparametric Identification

6 Nonparametric Identification (cont.) Problem set 1 due
7 Input Design, Persistence of Excitation, Pseudo-random Sequences Problem set 2 out
8 Input Design, Persistence of Excitation, Pseudo-random Sequences (cont.)

9 Least Squares, Statistical Properties

10 Least Squares, Statistical Properties (cont.)

Problem set 2 due

Problem set 3 out

11 Parametrized Model Structures, One-step Predictor, Identifiability

12 Parametrized Model Structures, One-step Predictor, Identifiability (cont.)

13 Parameter Estimation Methods, Minimum Prediction Error Paradigm, Maximum Likelihood

Problem set 3 due

Problem set 4 out

14 Parameter Estimation Methods, Minimum Prediction Error Paradigm, Maximum Likelihood (cont.)

15 Convergence and Consistency, Informative Data, Convergence to the True Parameters

16 Convergence and Consistency, Informative Data, Convergence to the True parameters (cont.) Problem set 4 due
17 Asymptotic Distribution of PEM

18 Asymptotic Distribution of PEM (cont.)

19 Instrumental Variable Methods, Identification in Closed Loop, Asymptotic Results

20 Instrumental Variable Methods, Identification in Closed Loop, Asymptotic Results (cont.) Problem set 5 out
21 Computation, Levinson Algorithm, Recursive Estimation

22 Computation, Levinson Algorithm, Recursive Estimation (cont.)

23 Identification in Practice, Error Filtering, Order Estimation, Model Structure Validation, Examples Problem set 5 due
24 Identification in Practice, Error Filtering, Order Estimation, Model Structure Validation, Examples (cont.)

Course Info

Learning Resource Types

notes Lecture Notes