- Docente: Riccardo Rovatti
- Credits: 6
- SSD: ING-INF/01
- Language: English
- Moduli: Riccardo Rovatti (Modulo 1) Mauro Mangia (Modulo 2) Mauro Mangia (Modulo 3)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2) Traditional lectures (Modulo 3)
- Campus: Bologna
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Corso:
Second cycle degree programme (LM) in
Advanced Automotive Electronic Engineering (cod. 9238)
Also valid for Second cycle degree programme (LM) in Electronic Engineering (cod. 0934)
Learning outcomes
The course aims at reviewing basic concepts of probability, operator theory and optimization and using them in the development of fundamental signal processing methods ranging from filtering to spectrum estimation, linear prediction, adaptive sampling and dimensionality reduction.
Course contents
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
Office hours
See the website of Riccardo Rovatti
See the website of Mauro Mangia
See the website of Mauro Mangia