LEARNING OUTCOMES

Basic principles of signals and linear systems. Spectral analysis of continuous signals; discrete signals; sampling and analogic to digital conversion. 
Random phenomena theory: probability, random variables, random processes. PAM, PCM, and analog modulations. Transmission techniques on noisy channels. 

AIMS AND LEARNING OUTCOMES

In the first semester the course aims to provide students with the theory of processing of continuous signals and corresponding systems with particular reference
to the Fourier transform, to the frequency analysis of periodic signals and Linear Time Invariant systems (LTI).
The sampling is therefore introduced both ideally and in its real versions, along with quantization and the conversion of signals using the PCM technique. The problem of discrete transmission is then dealt with by PAM technique and by multiplexing both in time and in frequency.

The theory of random phenomena is presented in the second semester, which is composed of the three parts of probability, random variables and random processes. The problem of the band-pass transmission on noisy channels is therefore addressed, describing linear modulations, AM, DSB and SSB, and angular modulations, FM and PM. 

At the end of the course the student will have to

- learn the theoretical basis of the analysis and processing of continuous signals;
- leran and know how to use the continuous Fourier transform; 
- know how to transform the graphic description of periodic signals into an analytical formula  both in time and in frequency;
- know under which conditions the ideal and real sampling allows the exact  signal reconstruction;
- know how to calculate the parameters that allow the exact reconstruction after sampling carried out through periodic functions;
- learn and be able to use the LTI system description to solve problems  both in terms of impulse response and frequency response;
- know and be able to use the theory of random phenomena;
- learn and know how to use the theory of analog band-pass transmissions.