VEMIVIM133P
1st semester of 2021/2022
Lecture-tutorial: Friday 10:00-12:30, I/413
Laboratory: Friday 10:00-12:30, I/413
Possible online education will be held using MS Teams for which personal invitations will be sent.
The homework should be submitted electronically to the e-mail address of the lecturers.
The deadline is the starting time of the next occasion (Friday at 10:00am).
Lecturers-Tutors: Prof. Katalin Hangos ( This email address is being protected from spambots. You need JavaScript enabled to view it.)
Anna Ibolya Pózna ( This email address is being protected from spambots. You need JavaScript enabled to view it.)
Course evaluation
The evaluation is based upon a mid-semester closed-book exam and on a parameter estimation project work to be implemented in MATLAB.
The pre-requisite of the course signature is
-- to submit to the given deadline at least 90% of the homework specified on the lectures-tutorials-laboratories,
-- to submit the project results and documentation to the given deadline, and
-- to achieve at least 50% on the closed-book exam.
Results: here
Lecture notes created under the EFOP-3.4.3 project:
- all slides in one file
-
Course contents
| Week | Date | Type | Material | Slides/supplements |
| 0 | 10 Sept | Registration week | ||
| 1 * | 17 Sept | Lec/tut | Recalling the basic knowledge on scalar and vector valued random variables, their properties and independence. The basics of mathematical statistics: sample, statistics-estimation. The estimation of mean value, covariance and correlation. |
|
| 2 | 24 Sept | Lec/tut Lab |
MATLAB basics. Simple functions for estimating mean value, covariance and correlation. |
PE_ComLab1.mlx |
| 3 * | 1 Oct | Lec/Tut | The properties of the estimates. Parameter estimation of static models. Linear regression and its properties. | |
| 4 | 8 Oct | Lab | Linear regression and its properties. |
PE_ComLab2.mlx |
| 5 * | 15 Oct | Lec/Tut | Discrete time stochastic processes, the input-output models of discrete time stochastic linear time-invariant systems. The principle of parameter estimation in dynamic case. | |
| 6 | 22 Oct | Lec/Tut | Methods that are based on minimization of the prediction error. Methods based on least squares (LS) minimization. The properties of the LS estimation method. | |
| 7 | 29 Oct | - | Holiday | |
| 8 | 5 Nov | Lab | Methods based on least squares (LS) minimization. |
PE_ComLab3.mlx arx_data.mat |
| 9 * | 12 Nov | Lec/Tut | Special parameter estimation methods. The instrumental variable (IV) method. Parameter estimation for nonlinear models. | |
| 10 | 19 Nov | Lab | Parameter estimation for nonlinear models. The instrumental variable (IV) method. |
PE_ComLab4.mlx Lab4-data.mat |
| 11 | 26 Nov | Lec/Tut | The practical implementation of parameter estimation. Project work specification. Consultation. | |
| 12 | 3 Dec | Lec/Tut Lab |
CLOSED BOOK EXAM Consultation for the project work |
|
| 13 | 10 Dec | Consultation for the project work | ||
| 14 | 17 Dec | Submission DEADLINE of the PROJECT WORK |