First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
Faculty of Engineering
ELECTRONIC ENGINEERING
Course unit
ESTIMATION AND FILTERING
IN04119565, A.A. 2011/12

Information concerning the students who enrolled in A.Y. 2010/11

Information on the course unit
Degree course Second cycle degree in
ELECTRONIC ENGINEERING
IN0520, Degree course structure A.Y. 2008/09, A.Y. 2011/12
N0
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination ESTIMATION AND FILTERING
Website of the academic structure http://moodle.dei.unipd.it/
Mandatory attendance No
Language of instruction Italian
Branch PADOVA
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge STEFANO PINZONI ING-INF/04

Mutuating
Course unit code Course unit name Teacher in charge Degree course code
IN04119565 ESTIMATION AND FILTERING STEFANO PINZONI IN0527

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines ING-INF/04 Automatics 9.0

Course unit organization
Period Second semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 9.0 72 153.0 No turn

Calendar
Start of activities 05/03/2012
End of activities 16/06/2012
Show course schedule 2019/20 Reg.2019 course timetable

Examination board
Board From To Members of the board
3 2012 01/10/2012 15/03/2014 PINZONI STEFANO (Presidente)

Syllabus
Prerequisites: Elements of probability theory, random variables and stochastic processes.
Elements of signals and systems theory: Fourier and Z-transform.
Dynamical models in state-space form.
Target skills and knowledge:: To know and to be capable of using the principal methods of statistical signal processing, with applications to different fields of engineering.
Course unit contents:
Planned learning activities: Bayesian estimation, minimum error variance linear estimators.
Linear filters for signal estimation: predictors, interpolators and reconstructors.
Wiener-Kolmogorov filters. Spectral factorization and ARMA models.
Minimum variance stochastic control.
State models. Kalman filter and its implementation. Extended Kalman filter.
Using MATLAB software.
Textbooks: G. Picci, Filtraggio statistico (Wiener, Levinson, Kalman) e applicazioni. Padova: Lib. Progetto, 2007. Cerca nel catalogo
Teaching methods: Traditional.
Assessment criteria: Homework, MATLAB papers, written exam.
Further information: