First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
ICT FOR INTERNET AND MULTIMEDIA
Course unit
DIGITAL SIGNAL PROCESSING
INP7079338, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
ICT FOR INTERNET AND MULTIMEDIA
IN2371, Degree course structure A.Y. 2017/18, A.Y. 2018/19
N0
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Degree course track ICT FOR LIFE AND HEALTH [004PD]
Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination DIGITAL SIGNAL PROCESSING
Department of reference Department of Information Engineering
E-Learning website https://elearning.dei.unipd.it/course/view.php?idnumber=2018-IN2371-004PD-2018-INP7079338-N0
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit can 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 GIANCARLO CALVAGNO ING-INF/03

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
INP7079338 DIGITAL SIGNAL PROCESSING GIANCARLO CALVAGNO IN2371
INP7079338 DIGITAL SIGNAL PROCESSING GIANCARLO CALVAGNO IN2371
INP7079338 DIGITAL SIGNAL PROCESSING GIANCARLO CALVAGNO IN0520
INP7079338 DIGITAL SIGNAL PROCESSING GIANCARLO CALVAGNO IN0521
INP7079338 DIGITAL SIGNAL PROCESSING GIANCARLO CALVAGNO IN0527
INP7079338 DIGITAL SIGNAL PROCESSING GIANCARLO CALVAGNO IN2371
INP7079338 DIGITAL SIGNAL PROCESSING GIANCARLO CALVAGNO IN2371

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses ING-INF/03 Telecommunications 9.0

Course unit organization
Period First semester
Year 1st 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 01/10/2018
End of activities 18/01/2019

Examination board
Board From To Members of the board
2 A.A. 2018/2019 01/10/2018 15/03/2020 CALVAGNO GIANCARLO (Presidente)
ZANUTTIGH PIETRO (Membro Effettivo)
BADIA LEONARDO (Supplente)
CORVAJA ROBERTO (Supplente)
ERSEGHE TOMASO (Supplente)
LAURENTI NICOLA (Supplente)
MILANI SIMONE (Supplente)
ROSSI MICHELE (Supplente)
TOMASIN STEFANO (Supplente)
VANGELISTA LORENZO (Supplente)
ZANELLA ANDREA (Supplente)
ZORZI MICHELE (Supplente)

Syllabus
Prerequisites: Previous knowledge of the following topics is expected: Calculus, Linear Algebra, Probability, Random Variables and Stochastic Processes, Signals and Systems, basic elements of the Matlab programming language.
Target skills and knowledge: The educational goal of the course is to provide the following knowledge and skills:
1. To rehears and consolidate the basic concepts of digital signal processing that the student should already know from previous studies (e.g., Signals and Systems).
2. To learn the possible practical applications of the previous concepts in communications and multimedia systems.
3. To learn advanced notions of digital signal processing, among which are:
3.a. To know how to design both FIR and IIR digital filters;
3.b. To be able to design interpolation/decimation systems for digital signals;
3.c. To know how to perform the spectral analysis od digital signals.
4. To be aware of the many practical examples of application of digital signal processing systems which are essential or useful in several areas of the Information and Communications Technology.
5. To be able to develop computer simulation algorithms for the implementation of digital signal processing, and to asses if the given design specifications are met.
Examination methods: The grading of the expected knowledge and skills is based on two contributions:
1. A closed book written exam, where the student must solve 4 problems, needed to verify that a good knowledge of the theoretical aspects and of the fundamental characteristics of the various digital signal processing systems analyzed during the course has been acquired.
2. The development of a simple home assignment consisting in a computer simulation project using Matlab, to check the ability of the student to apply the theoretical concepts to a practical implementation. Each student must write a short report describing the methodologies used to solve the assigned project and the obtained results.

The written exam contributes 85% to the final score, while the project contributes 15% to the final score.
Assessment criteria: The evaluation criteria with which the verification of the knowledge and expected skills is carried out considers the following aspects:
1. The completeness and the degree of detail of the acquired knowledge of digital signal processing basics.
2. The ability to analyze advanced digital signal processing systems.
3. The ability to design digital signal processing systems.
4. The skill to apply the acquired theory to identify the appropriate tools for the design and the computer simulation of digital signal processing systems to be used in the various areas of the Information and Communications Technology.
Course unit contents: Shift-invariant discrete time linear systems: convolution; stability; causality; systems defined by linear constant coefficient difference equations; FIR and IIR linear time-invariant filters.
Z-transform and its properties; transfer function and frequency response. All-pass transfer functions. Simple examples of low-pass/high-pass, band-pass/band-stop, and all-pass transfer functions.
Linear phase FIR filters.
Discrete Fourier Transform (DFT): definition, properties and usage in practical contexts; FFT algorithms; fast convolution algorithms.
Design of linear phase FIR filters: windowed Fourier series technique; frequency sampling method; minimization of the Chebyschev norm (Remez algorithm).
IIR filter design using the bilinear transformation method; Butterworth, Chebyschev and Cauer filters; frequency transformations.
Direct form, cascade, and parallel realizations.
Multirate linear systems: interpolation and decimation; efficient realizations.
Examples of application.
Planned learning activities and teaching methods: Teaching is provided by means of lectures at the chalkboard, since we believe that this way of teaching allows to keep the right rate (speed) in the presentation of the different topics and to maintain the student attention high, with the possibility of interaction and participation.
The simulation results of some simple digital signal processing systems and the results relative to the design of several digital filters by means of Computer Aided Design tools are shown using a computer and visualized on large screen.
Additional notes about suggested reading: All the topics of the course will be taught in classroom. Class notes can be integrated with the reference textbook and with additional material made available on the moodle platform.
Sets of suggested problems (homework) are made available on the moodle platform and their solutions are presented later.
Textbooks (and optional supplementary readings)
  • S. Mitra, Digital Signal Processing: a Computer-based Approach. New York: McGraw-Hill, 2011. Cerca nel catalogo
  • A.V. Oppenheim, R.W. Schafer, Discrete-Time Signal Processing. Harlow, Hessex: Pearson, 2014. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Loading of files and pages (web pages, Moodle, ...)
  • Suggested problems with postponed solutions.

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • Matlab

Sustainable Development Goals (SDGs)
Quality Education Industry, Innovation and Infrastructure