DIPARTIMENTO DI INGEGNERIA INDUSTRIALE E DELL'INFORMAZIONE
Corso di studio
Space Communication and Sensing
Primo Semestre (01/10/2018 - 18/01/2019)
50 ore di attività frontale
SCRITTO E ORALE CONGIUNTI
Basic concepts in continuous time signal theory.
Mathematical treatment of time-discrete signals and systems:
. Z-transform of signals represented by difference equations;
. design of digital filters for deterministic and stochastic signals;
. spectrum estimation for discrete-time signals;
. optimal filtering and adaptive filter design.
Programma e contenuti
Introduction to digital signal theory.
Discrete time signals, sampling theorem, linear shift invariant digital systems.
Analysis of digital systems in the Fourier and Z transform domains.
Discrete-time random processes.
Digital filtering of deterministic and stochastic signals.
Deterministic and stochastic signal modeling.
Wiener Filter: linear prediction, white noise filtering, unwanted signal canceling.
Adaptive filtering: LMS, RLS and Kalman algorithms.
Application examples in Matlab and programmable hardware platforms.
Lectures (hours/year in lecture theatre): 44
Practical class (hours/year in lecture theatre): 0
Practicals / Workshops (hours/year in lecture theatre): 8
Testi di riferimento
Monson H. Hayes Statistical Digital Signal Processing and Modeling. John Wiley & Sons Inc, 1996.
Modalità verifica apprendimento
The exam consists of an oral test during which questions will be asked on two/three different topics regarding the basic mathematical techniques, signal characterization, and filtering, in order to cover most of the course topics.
Alternatively, each student can choose to implement a laboratory project, assigned by the teacher, followed by an in-depth interview. The assigned projects will cover most of the course topics.
The final mark is in thirtieths.
Obiettivi Agenda 2030 per lo sviluppo sostenibile