Anno Accademico 2020/2021
- Docente: Riccardo Rovatti
- Crediti formativi: 6
- SSD: ING-INF/01
- Lingua di insegnamento: Inglese
- Moduli: Riccardo Rovatti (Modulo 1) Mauro Mangia (Modulo 2)
- Modalità didattica: Convenzionale - Lezioni in presenza (Modulo 1) Convenzionale - Lezioni in presenza (Modulo 2)
- Campus: Bologna
-
Corso:
Laurea Magistrale in
Ingegneria elettronica (cod. 0934)
Valido anche per Laurea Magistrale in Advanced automotive electronic engineering (cod. 9238)
Conoscenze e abilità da conseguire
The course aims to give students the appropriate techniques for the acquisition and processing of real world data and the implementation of efficient and robust signal processing structures. Knowledge about the modern theory and practice of sampling from an engineering perspective, and classical and modern signal processing tools will be acquired.
Contenuti
Random varibles and vectors
Expectation
Moments and generating function
Covariance
Stochastic processes
Joint probability
Correlations and covariances
Projections
Static linear processing of random vectors
Quantization of random variables
Linear filtering of stochastic processes
z-transform
Structure and model for discrete-time linear filters
Stability
Design methods for discrete-time linear filters
Gaussian random vectors
Gaussian stochastic processes, white noise
Power spectrum
Wiener-Khinchin theorem
Elements of estimation theory
Periodogram spectral estimation
Modified-periodogram spectral estimation
Estimation of correlation
Minimum-variance spectral estimation
Linear prediction
Orthogonality principle
Yule-Walker equations
Finite-memory processes
Finite Markov chains
Orario di ricevimento
Consulta il sito web di Riccardo Rovatti
Consulta il sito web di Mauro Mangia