Università degli Studi di Napoli "Parthenope"

  1. Teaching
  2. COMPUTER SCIENCE, BIOMEDICAL AND TELECOMMUNICATIONS ENGINEERING
  3. PROBABILITY AND RANDOM

Stampa

PROBABILITY AND RANDOM

Teaching schedule

Academic year: 
2018/2019
Belonging course: 
Course of Bachelor's Degree Programme on COMPUTER SCIENCE, BIOMEDICAL AND TELECOMMUNICATIONS ENGINEERING
Location: 
Napoli
Disciplinary sector: 
TELECOMMUNICATIONS (ING-INF/03)
Language: 
Italian
Credits: 
9
Year of study: 
3
Cycle: 
First Semester
Hours of front activity: 
72

Language

Italian.

Course description

This course is designed to motivate the students for use of probabilistic models in engineering analysis and design, to equip the students with the basics of probability theory and to introduce commonly used probabilistic models and their applications.

Knowledge and understanding:fundamentals of the theory of probability, models of RVs and their transformation, random processes (continuous and discrete time) and their energetic characterisation, acf.
Applying knowledge and understanding: the student must be able to analyse random phenomena, to apply the fundamentals of the theory of probability to solve simple problems, to manage random vectors and signals, to calculate the PSD and ESD.
Making judgements: the student must be able to identify the main techniques to analyse a random phenomenon.
Communication skills: the student must be able to explain the subjects of the course, by using the precise scientific language.
Learning skills: the student must be able to consult books and papers different from those adopted by the teacher.

Prerequisites

Mathematics, Fundamentals of Algebra and Geometry, and Signal Theory.

Syllabus

Probability (9h lessons+3h exercises): Sets, events, and probability. Random variables (19h lessons+10h exercises+ 3h Matlab): Random variables, discrete and continuous distributions. Distributions of functions of a random variable. Expected values and moments. Common families of distributions. Multiple random variables (7h lessons+4h exercises + 2h Matlab): Joint and marginal distributions. Conditional distributions and independence. Covariance and correlation. First elements of information theory. Random processes (10h lessons+5h exercises): Random processes. Expectation and acf. Bernoulli process. Stationarity. Cyclostationarity. ESD. PSD. PAM signal. Relationship between acf at the input and output of LTI systems. Theorem of Wiener-Kinchine. Gaussian processes.

Probability (9h lessons+3h exercises): Sets, events, and probability. Random variables (19h lessons+10h exercises+ 3h Matlab): Random variables, discrete and continuous distributions. Distributions of functions of a random variable. Expected values and moments. Common families of distributions. Multiple random variables (7h lessons+4h exercises + 2h Matlab): Joint and marginal distributions. Conditional distributions and independence. Covariance and correlation. First elements of information theory. Random processes (10h lessons+5h exercises): Random processes. Expectation and acf. Bernoulli process. Stationarity. Cyclostationarity. ESD. PSD. PAM signal. Relationship between acf at the input and output of LTI systems. Theorem of Wiener-Kinchine. Gaussian processes.

Teaching Methods

- Lectures;
- exercises.

Textbooks

[1] Giacinto Gelli - Probabilità e informazione (fifth version, September 2003). [2] Athanasios Papoulis - Probability, Random Variables, and Stochastic Processes, ed. McGraw-Hill, third edition. [3] Alberto Leon-Garcia, "Probability and Random Processes for Electrical Engineering", ed. Addison-Wesley, second edition. Additional PFA lectures are available on the website edi.uniparthenope.it.

Learning assessment

Final exam:
- written test;
- oral test.

More information

Lectures are in Italian. The professor is fluent in English and is available to interact with students in English, also during the examination.