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   +(36) 88 624 023 | |    H-8200, Veszprem, Egyetem str. 10, Building I.

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Lecturers: Hangos Katalin professor emerita, Magyar Attila professor


The subject assumes knowledge of the following subjects and builds on them:

Signal processing

Discrete and continuous systems



Students acquire knowledge related to the following topics, taking into account their individual training plan and interests:  


T1. Parameter estimation of dynamical systems 

model structure and parameter estimation, the general parameter estimation problem and its properties, least squares estimations and their properties, curve fitting using the least squares method, unbiasedness and effectiveness of estimations


T2. Modern system identification methods

maximum likelihood estimates and their properties, Bayes estimates and their properties, methods and properties of auxiliary variables, identification of nonlinear systems, recursive parameter estimation methods and their properties


T3. Filtering 

methods of signal filtering and change detection, methods of state estimation of dynamic systems, the Kalman filter and its extensions.


The evaluation is based on the development of an individual project task related to the above topics. 



Hangos, K.M., Szederkényi, G. (1999). Dinamikus rendszerek paramétereinek becslése, Veszprémi Egyetemi Kiadó 

Hangos, K.M., Bokor, J., Szederkényi, G. (2002). Computer controlled systems,  Veszprémi Egyetemi Kiadó, Veszprém

Ljung, L. (1999). System Identification: Theory for the User, Prentice Hall