Università di Pavia - Offerta formativa

DIGITAL SIGNAL PROCESSING

Anno immatricolazione

2019/2020

Anno offerta

2020/2021

Normativa

DM270

SSD

ING-INF/03 (TELECOMUNICAZIONI)

Dipartimento

DIPARTIMENTO DI INGEGNERIA INDUSTRIALE E DELL'INFORMAZIONE

Corso di studio

ELECTRONIC ENGINEERING

Curriculum

Microelectronics

Anno di corso

2°

Periodo didattico

Primo Semestre (28/09/2020 - 22/01/2021)

Crediti

6

Ore

50 ore di attività frontale

Lingua insegnamento

English

Tipo esame

ORALE

Docente

SAVAZZI PIETRO (titolare) - 6 CFU

Prerequisiti

Basic concepts in analog signal processing, spectral analysis and filtering.

Obiettivi formativi

Developing a strong working knowledge on signal processing algorithms for modeling discrete-time signals, designing optimum digital filters, estimating the power spectrum of a random signal, and designing and implementing adaptive filters.

Ability to implement the studied algorithms in Matlab standalone and hardware-oriented applications.

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.

Spectrum estimation.

Application examples in Matlab and programmable hardware platforms.

Metodi didattici

The course is based on lectures, practical exercises, case studies, and project examples, aimed at describing applications of statistical digital signal processing to practical utility projects.

Lectures (hours/year in lecture theatre): 44

Practicals / Workshops (hours/year in lecture theatre): 8

Lectures (hours/year in lecture theatre): 44

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 main course objectives, i.e., signal modeling, adaptive filtering, and spectrum estimation, 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.

Altre informazioni

Obiettivi Agenda 2030 per lo sviluppo sostenibile