First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
Course unit
INP9086622, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course Second cycle degree in
IN2371, Degree course structure A.Y. 2019/20, A.Y. 2019/20
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Degree course track TELECOMMUNICATIONS [001PD]
Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination DIGITAL SIGNAL PROCESSING
Department of reference Department of Information Engineering
Mandatory attendance No
Language of instruction English
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

Teacher in charge TOMASO ERSEGHE ING-INF/03

Course unit code Course unit name Teacher in charge Degree course code

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses ING-INF/03 Telecommunications 6.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 6.0 48 102.0 No turn

Start of activities 30/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2019 course timetable

Examination board
Board From To Members of the board
1 A.A. 2019/2020 01/10/2019 15/03/2021 ERSEGHE TOMASO (Presidente)
BADIA LEONARDO (Membro Effettivo)


Common characteristics of the Integrated Course unit

Prerequisites: This course has the following prerequisites: fundamentals of signals and systems, knowledge on Fourier analysis, and basics of Computer Programming in any language which is appropriate for signal analysis (e.g., MatLab, Python, C, Java). Moreover: 1. for the DIGITAL SIGNAL PROCESSING module: Laplace and/or Z transforms; 2. for the E-HEALTH module: fundamentals of telecommunications and of network protocols; any further knowledge or previous experience on telemedicine and biological signals acquisition or processing is also useful.
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
2. To be aware of the many practical examples of application of digital signal processing systems which are essential or useful in several areas of ICT and multimedia
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 of digital signals
4. To be able to develop computer simulation algorithms for the implementation of digital signal processing systems, and to asses if the given design specifications are met

E-HEALTH module:
1. To apply fundamentals of signal processing to biosignals and bioimages
2. To know telemedicine/wireless body area network (WBAN) components and architectures, including the most common solutions
3. To know existing standards and regulations for telemedicine/WBAN systems
4. To evaluate the performance of existing telemedicine/WBAN systems, based on their context differences and effectiveness
5. To know the main scenarios of application, possibly in cross-disciplinary contexts, of the techniques studied
6. To be aware of future perspectives, directions and challenges of this field
Examination methods: The course has the following methods of examination:

The grading of the expected knowledge and skills is based on two contributions: 1. a closed book WRITTEN EXAM, where the student must solve four 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 HOMEWORK 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 homework and the obtained results.

E-HEALTH module:
For ATTENDING STUDENTS the verification of the expected knowledge and skills is carried out with: 1. an ORAL EXAM (individual assessment) with few questions to test the knowledge of the whole course program; 2. a simple PROJECT (5-6 pages) on a selected topic to be agreed with the teacher; the project is presented in about 15 minutes (using slides) during the oral exam; 3. a two-pages report at the end of each LAB EXPERIENCE. Projects and lab experiences are carried out either individually or in pairs at the discretion of the teacher.

For NON-ATTENDING STUDENTS the verification of the expected knowledge and skills is carried out with: 1. an ORAL EXAM (individual assessment) with few questions to test the knowledge of the whole course program; 2. a more complex PROJECT on a selected topic to be agreed with the teacher; the project requires both a theoretical part and a Matlab-based part in order to test the abilities developed by the attending students during laboratories; the project is presented in about 15 minutes (using slides) during the oral exam.

The final grade of the course is expressed as a combination of the judgments in the two modules (50%+50%).
Assessment criteria: The evaluation criteria with which the verification of knowledge and expected skills will be carried out will be:

1. Completeness of the acquired knowledge about digital signal processing basics
2. Property in the technical terminology used
3. Ability in the design and analysis of advanced digital signal processing systems, to be used in the diverse areas of ICT and multimedia
4. Skill in applying the acquired theory to identify the appropriate tools for designing and testing (via computer simulations) a digital signal processing system

E-HEALTH module:
1. The completeness of the acquired knowledge
2. The skill to analyze a telemedicine/WBAN system based on such knowledge
3. The correct use of the technical terminology, both in the project and in the oral assessment
4. The skill to autonomously derive conclusions from numerical results obtained from simulations or measurement campaigns
5. The skill to use ICT tools in the evaluation of telemedicine/WBAN systems and their main parameters
6. The skill to synthesize key points of different topics during the oral assessment and the quality of the oral presentation
7. The skill to effectively work with the partner during lab experiences and project development

Specific characteristics of the Module

Course unit contents: The module will cover the following topics:
1. Shift-invariant discrete time linear systems; Systems defined by linear constant coefficient difference equations; Z-transform and its properties.
2. Discrete Fourier Transform (DFT): definition, properties and usage in practical contexts; FFT algorithms; fast convolution algorithms.
3. Design of linear phase FIR filters: windowed Fourier series technique; frequency sampling method; minimization of the Chebyschev norm (Remez algorithm).
4. IIR filter design using the bilinear transformation method; Butterworth, Chebyschev and Cauer filters; frequency transformations.
5. Multirate linear systems: interpolation and decimation; Efficient realizations; Examples of application.
Planned learning activities and teaching methods: The module includes:
- 20 lectures which will give an overview of the main subjects and methodologies, a discussion on the main scenarios of application, and a deeper mathematical analysis on the subjects introduced;
- 4 laboratory lectures to guide students to the use of computer programs for digital signal processing (MatLab).

The frontal teaching activities involve the use of tablet computers (transparencies + digital ink).
Additional notes about suggested reading: All the topics of the course will be taught in the classroom. All the teaching material presented during the lectures is made available on the platform "". Class notes can be integrated with the reference textbook and with additional material made available on the elearning platform.
Textbooks (and optional supplementary readings)
  • Oppenheim, Alan V.; Schafer, Ronald W., Discrete-time signal processingAlan V. Oppenheim, Ronald W. Schafer. Harlow: Essex, Pearson, 2014. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem based learning
  • Case study
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • One Note (digital ink)
  • Latex
  • Matlab

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