Lecturing and problem solving activities are taught in Italian.
EXTENDED PROGRAM
Introduction to stochastic processes [6/6]
Revision of probability theory: axiomatic definition, events, incompatibility, independence, conditional events, Total probability theorem, Bayes theorem. Random variables: pdf, distribution function, expectation (mean, variance). Join random variables: joint pdf, joint distribution, joint moments (correlation); independence of random variables; examples. Functions of random variables. Conditional random variables: conditional pdf, conditional expected values. Repeated trials. Law of large numbers. Poisson distribution. Central Limit Theorem.
Stochastic processes. Stationarity and ergodicity. Auto-correlation of a random process (definition and examples, periodogram method). Power spectral density of a random process. Wiener-Khintchine theorem. Sample processes and their statistical modelling (random phase sinusoid, gaussian, PAM, ...). Noise (white, colored, narrow-band...).
Complements of analog signal processing [4/4]
LTI filtering of random processes. Parametric systems. Non linear systems. Ideal transmission system. Harmonic and crossmodulation distortion measures. Non linear processing of a random process. Memoryless non linear processing of a random process. Sum and multiplication of random processes.
Fundamentals of analog modulation [2/2]
Amplitude modulation (AM, DSB, SSB, VSB). Coherent demodulation and envelop demodulation. Quadrature amplitude modulation. FDM. Frequency modulation systems. Modulated signal spectrum. Inter-symbol interference.
Digital representation of an analog signal [3/3]
Wrap-up on signal sampling; Quantization; quantization noise: statistical properties. Real A/D and D/A conversions; limit cycle of an A/D converter.
Examples of real systems.