Objective of this course is to provide knowledge about: fundamentals of probability theory, random variables, periodic and aperiodic deterministic signals, random processes, filtering of deterministic signals and random signals
At the end the student will be able to
- model random experiments and derive their characteristic parameters making use, if appropriate, of random variables
- analyze signals (both determined and random) in time and frequency domains
- derive characteristic features of signals (both deterministic and random) in output of linear time-invariant systems starting from the characterization of the signals and of the system itself
Lectures for theory and exercises
Deterministic signals: fundamentals, properties, representation in the time and frequency domain, Fourier transforms, systems, linear and time invariant systems, signal filtering.
Probability theory: fundamentals, random experiments and probability laws, random variables, transformation of random variables, systems of random variables.
Random signals: fundamentals, properties, characterization in the time and frequency domains, random signal filtering, noise, Markov processes
M. Luise, G. Vitetta. Teoria dei segnali. McGraw Hill.