Fundamentals of Mechanisms of Systems (since 2022-23)

Fundamentals of Mechanisms of Systems (since 2022-23)
3 YEAR 1 semester 9 CREDITS



  Code: 8037957 (ex KDM)
Code: 8039957 (FMS)


LEARNING OUTCOMES: The course aims to teach students the knowledge and tools that are needed to address the issues that are related to the identification, modeling, analysis, design of multi-body planar systems, and in particular some transmission organs in English language and terminology

KNOWLEDGE AND UNDERSTANDING: modeling and procedures to recognize the structure and characteristics of mechanisms and machines

APPLYING KNOWLEDGE AND UNDERSTANDING: acquisition of analysis procedures for the understanding of kinematic and dynamic characteristics of mechanisms and machines

MAKING JUDGEMENTS: possibility of judging the functionality of mechanisms and machines with their own qualitative and quantitative assessments

COMMUNICATION SKILLS: learning of technical terminology and procedures for presenting the performance of mechanisms

LEARNING SKILLS: learning of technical terminology and procedures for the presentation of the performance of mechanisms


  • Structure and classification of planar mechanical systems, kinematic modeling, mobility analysis, graphical approaches of kinematics analysis, kinematic analysis with computer-oriented algorithms, fundamentals of mechanism synthesis, trajectory generation; dynamics and statics modeling, graphical approaches of dynamics analysis, dynamic analysis with computer-oriented algorithms, performance evaluation; elements of mechanical transmissions with gears, belts, brakes, and flywheels.

Fundamentals of Telecommunications – (block C)

Fundamentals of Telecommunications – (block C)
3 YEAR 2 semester 9 CREDITS – 6 CREDITS* (2022-23)


Antonio Saitto

Francecsco Zampognaro

2019-20 (9 cfu)
2020-21 (9 cfu)
2021-22 (9cfu)


2022-23 (6 cfu)
  Code: 8039512

*the number of credits depends on your study plan. The Study plans A.Y. 22-23 changed in this way: FDC 6 CREDITS


LEARNING OUTCOMES: To provide basic knowledge on deterministic analogic signals, linear time invariant systems, analogic random processes, noise and signal to noise ratio, analogic modulation concepts. To allow practical experience on Matlab.
KNOWLEDGE AND UNDERSTANDING: Obtain capability to apply the acquired knowledge in the field of elementary analogue signal processing to approach and solve problems concerning more complex processing in the field of digital signals. Obtain capabilities to understand problem to approach the job in professional manner.
APPLYING KNOWLEDGE AND UNDERSTANDING: Obtain and demonstrate to understand problems of university degree of complexity both during the class and on books of equivalent level.
MAKING JUDGEMENTS: Acquire the capability to collect and analyse data on the analogue signal processing to carry out and express opinion autonomously and independently.
COMMUNICATION SKILLS: Acquire capability to explain what learnt to both skilled and not skilled people.
LEARNING SKILLS: Acquire such a capability to learn to be able to approach the following courses with high degree of autonomy.


Deterministic continuous-time signals
Introduction, telecommunication systems and services, definition of signals, ideal transmission of signals, time domain signals, complex notation, basic operations on signals, classification, duration, Dirac impulse, energy and power. Affinity: cross correlation and autocorrelation between energy and power signals. Time domain series representation of signals: Fourier series for periodic signals, representation with series of orthogonal functions,
Fourier series for time limited signals, representation with samples interpolation. Representation in the signal domain, Gram- Schmidt orthogonalization. Linear transformation: Fourier transform. Examples of Fourier transform, affinity for frequency represented signals, energy and power spectrum, sampling theorem in time and frequency domain. Representation in the complex domain: analytic signal and complex envelope. Basics of source signals: analogue and digital signals. Multilevel source signals, binary signals, synchronous and asynchronous signals. Linear transformation between signals, linear and time invariant transformations in one port systems and in two port systems. Ideal two port system, perfect two port systems. Fundamentals of transmission, ideal transmission, perfect transmission systems, perfect linear channels, time continuous linear processing, filters, processing and reverse processing of step signals, total processing. Multiplexing, analogue digital conversion, basics on channel coding, basics on modulation.
Time continuous random variables and stochastic processes. Random variables theory, probability distribution and density functions, conditional probability distribution. Moments, characteristic and generating function of a random variable. Functions of random variables, distribution and density functions computation, sequences of random variables, transformation of random variables, independence of random variables. Expected value, variance and covariance. Conditional density functions, complex random variables. Stochastic processes, generalities, properties and moments. Classification, spectral theory, transformation of stochastic processes. The Gaussian process. Stationary processes, cross correlation, sum of processes and complex process, ciclostationary processes of first and second order, processes represented by the complex envelope, stationary process not in base band, processes represented in time series, real processes with random factors, processes sampled in base band, complex processes with random factors. Gaussian processes: noise, Gaussian stationary noise not in base band, white Gaussian noise in the signal space. Markov processes: properties, continuous and discrete time.
Imperfect transmission Imperfect connection. Undesirable additive affect at the output. Imperfect transmission over linear time variant channel. Imperfect transmission over linear time invariant channel. Imperfect transmission over non linear channel. Imperfect transmission with independent disturbs. Generalities on independent disturbs. Reduction of effects from independent disturbs. System additive Gaussian noise. Power analysis of a transmission system. Single two port system. Power analysis of noisy linear two port system chain. Noisy linear two port systems. Receiver sensitivity.
Signals utilized in transmission systems Harmonic signals modulation. Transmitter and receiver general schemes for modulated harmonic signals. Analogue harmonic modulation. Amplitude modulations (AM). Angle modulations: phase (PM) and frequency (FM). Performance analysis of harmonic modulation systems with analogue signals. Performance of AM systems. Signal to noise ratio for PM and FM systems.
Signals lab Introduction to Matlab and its use to graphically represent signals. Execution of operations among signals (also periodic). Study of signal properties (energy and power) and correlations.

Networking and Internet – (block C)

Networking and Internet – (block C)
3 YEAR 2 semester 9 CREDITS
Prof. Luca Chiaraviglio 2019-20
  Code: 8039511


LEARNING OUTCOMES: Understand and master the architecture of the Internet.

KNOWLEDGE AND UNDERSTANDING: Understanding of the Internet architecture to: i) learn the economic, technological, historical and research pillars that stimulated the Internet growth, ii) acquire skills about the management of fixed, WiFi and cellular networks, iii) touch through a ground-truth approach about the relationship between security aspects and networking.

APPLYING KNOWLEDGE AND UNDERSTANDING: Practical aspects, such as: network dimensioning problems, performance evaluation, configuration of devices at application and networking levels.

MAKING JUDGEMENTS: The students will learn the building blocks of the current Internet. The students will also understand the current limitations and the possible future research topics.

COMMUNICATION SKILLS: The student will improve its communications skills thanks to the oral examination. Moreover, the adoption of laboratory experiences allows improving the team working skills to solve complex problems.

LEARNING SKILLS: The students will improve its learning skills, thanks to a step by step approach, in which the laboratory experiences support and strengthen the concepts detailed during the lessons. Moreover, the classroom proposes different practical research topics, which can be used as material for further investigations of Bachelor thesis.


ECxopree rTimopeinctsal Part with Netkit
– Introduction to the Internet
– Application Layer (HTTP, DHCP, DNS, email)
– Transport Layer (TCP, UDP)
– Network Layer (RIP, OSPF, BGP, SDN, IP, ICMP)
– Link Layer

Additional Topics
– Wireless and Mobile Networks (WiFi, 2G, 3G, 4G)
– Multimedia Networking (Streaming)
– Security (principles of criptography, SSL, WEP, secured email, certification autorithies)

Digital Signal Processing – (block C-D)

Digital Signal Processing – (block C-D)
3 YEAR 2 semester 6 CREDITS* – 9 CREDITS (22-23)
Prof. Marina Ruggieri 2019-20


Tommaso Rossi

2020-21 (6cfu)
2021-22 (6cfu)
2022-23 (9cfu)
  Code: 8039514

*the number of credits depends on your study plan. The Study plans A.Y. 222-23 changed in this way: DSP 9 CREDITS


LEARNING OUTCOMES: The course aims at providing to the students the theoretical and practical tools for the development of design capabilities and implementation awareness of Digital Signal Processing (DSP) systems and applications.

KNOWLEDGE AND UNDERSTANDING: Students are envisaged to understand the DSP theoretical, design and algorithm elements and to be able to apply them in design exercises.

APPLYING KNOWLEDGE AND UNDERSTANDING: Students are envisaged to apply broadly and, if applicable, to personalize the design techniques and algorithm approaches taught during the lessons.

MAKING JUDGEMENTS: Students are envisaged to provide a reasoned description of the design and algorithm techniques and tools, with proper integrations and links.

COMMUNICATION SKILLS: Students are envisaged to describe analytically the theoretical elements and to provide a description of the design techniques and the algorithm steps, also providing eventual examples.

LEARNING SKILLS: Students are envisaged to deal with design tools and manuals. The correlation of topics is important, particularly when design trade-offs are concerned.


PART 1- Discrete-time signals and systems; representation in the time domain; sampling process; Discrete-time Fourier transform (DTFT); Z-transform; Discrete Time Fourier Series (DTFS).
PART 2 – Processing algorthms: introduction to processing; Discrete Fourier Transform (DFT); finite and long processing; DFT-based Processing; Fast Fourier Transform (FFT); processing with FFT.
PART 3 – Filter Design: introduction to digital filters: FIR and IIR classification; structures, design and implementation of IIR and FIR filters; analysis of finite word length effects; DSP system design and applications; VLAB and applications (Dr. Tommaso Rossi) with design examples and applications of IIR and FIR filters, Matlab-based lab and exercises (optional).

VLSI Circuit and System Design – (block B)

VLSI Circuit and System Design – (block B)
3 YEAR 2 semester 9 CREDITS
Prof. Marco Re 2019-20
RE MARCO 2020-21
  Code: 8039166



The student will be able to analyze and design microprocessor systems and SW for microprocessors. Starting from these topics the student will be able to write a program in LC3 assembler and to interface the microprocessor with external devices.


The student will apply the knowledge and understanding developed to the analysis of practical problems. This would imply a critical knowledge in terms of silicon real estate and speed for microprocessor based systems.


The student will have to prove his critical awareness with respect to the simplifying assumptions useful to describe and analyze microprocessor systems as well as his critical awareness of the correct order of magnitude of performance parameters while dealing or designing microprocessor systems.

COMMUNICATION SKILLS: The student will prove, mostly during the oral test, his capacity of describing the operation and functioning of microprocessor based digital systems.

LEARNING SKILLS: The student will get familiar with the schematization of practical problems, mostly during the development of his skills for the written test. This mainly concerns microprocessor systems.


Basics of digital electronics
Data structures for microprocessor systems
The Von Neumann Architecture
The LC3 Architecture
Machine language programming of the LC3
LC3 Assembly programming
LC3 Traps e subroutines
Basics of C language programming
Instrumentation and measurements for microprocessor systems