Analog signals. Fourier series. Fourier transform. Linear systems. Random processes. Discrete-time signals. Sampling. Z transform. LTI systems. DFT and FFT. Signal transmission: analog and digital systems. Applications.
[1] Argenti F., Mucchi L., Del Re E., Elaborazione numerica dei segnali: Teoria, esercizi ed esempi al calcolatore, McGraw-Hill, 2011.
[2] Gherardelli M., Fossi M., Appunti di teoria dei segnali: Segnali deterministici, segnali aleatori. Società Editrice Esculapio, Bologna. Seconda Edizione, 2016.
[3] Luise M., Vitetta G.M., Teoria dei segnali, McGraw-Hill, 2003.
[4] Proakis J.G., Salehi M.: Communication Systems Engineering, Prentice Hall International Editions.
Learning Objectives
The aims of the course are the following:
Providing tools and methods for the representation of deterministic and random processes for both analog and discrete-time signals. Introducing the sampling problem and the processing of discrete-time signals. Introducing the basic concepts of signal transmission and of modern telecommunications systems. Introducing the principal applications of digital signal processing.
At the end of the course, the student should be able to analyze and characterize signals and systems both in the time and in the frequency domain, know the principal effects of sampling, design simple discrete-time systems and understand basic principles of the applications in the telecommunications field.
Prerequisites
Limits, series, integrals. Complex analysis. Linear algebra. Trigonometry. Probability theory. Random variables.
Teaching Methods
Lectures
Further information
No slides are used
Type of Assessment
The exam takes place in two tests. The first test consists in (at the student's choice): two written partial tests, carried out during the course (on the part of the program carried out until the test date); or in a single written exam on all the subjects of the course. The second test consists of an oral examination (mandatory).
Course program
Introduction and classification of signals (analog and discrete-time, random and deterministic).
Linear spaces of functions. Hilbert spaces, distance, norm, inner product, orthonormal bases. Approximations in Hilbert spaces.
Fourier series. Definition and properties. Complex form of the Fourier series. Spectrum of signals.
Fourier transform and its properties. Convolution of signals. Dirac's function.
Linear systems. Impulse and frequency response.
Random processes and their characterization.
Sampling. Discrete-time Fourier transform and its properties. Quantization.
Z transform and its properties.
Linear time-invariant (LTI) systems. Impulse response, transfer function, frequency response. Linear finite difference equations.
Discrete Fourier Transform. Circular convolution.
Examples and applications of digital signal processing. Modulation and transmission of signals.