Signal Processing
A.Y. 2018/2019
Learning objectives
Il corso si pone l'obiettivo di fornire le competenze di base dell'elaborazione numerica dei segnali digitali. Oltre ai fondamenti teorici, si affronteranno le principali tecniche di analisi e filtraggio dei segnali numerici, anche attraverso alcuni strumenti software (Matlab).
Expected learning outcomes
Undefined
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
· Introduction. Continuous-time and discrete-time signals. Systems. Review of complex numbers. Phasors.
· Time-continuous sinusoidal signals. Frequency. Harmonic frequencies and periodical signals.
· Digital signals: sampling and quantization. Sampling of continuous-time signals and the sampling theorem. Aliasing. Reconstruction of continuous-time signals from samples and interpolation.
· Analysis of discrete-time signals in the frequency domain. Discrete-time Fourier Transform (DTFT), Discrete Fourier Transform (DFT) and FFT algorithm. Spectral characterization of sampled signals.
· Linear time-invariant systems (LTI). Impulse response. Stability and causality. Systems interconnection (series, parallel, feedback). Finite-difference equations as representation of LTI systems.
· Zeta transform. Definition and principal properties. Region of convergence. Analysis of LTI systems via Zeta transform. Transfer functions, poles and zeros. Frequency response. Stability condition in the Zeta domain
· FIR filters. Linear phase and LTI filter with symmetrical impulse response. FIR filters design with the window method.
· IIR filters. Design by poles and zeros placement. Design of digital IIR filters starting from their analog counterparts.
Warning: the class is taught in Italian. The course program is provided for reference only.
· Time-continuous sinusoidal signals. Frequency. Harmonic frequencies and periodical signals.
· Digital signals: sampling and quantization. Sampling of continuous-time signals and the sampling theorem. Aliasing. Reconstruction of continuous-time signals from samples and interpolation.
· Analysis of discrete-time signals in the frequency domain. Discrete-time Fourier Transform (DTFT), Discrete Fourier Transform (DFT) and FFT algorithm. Spectral characterization of sampled signals.
· Linear time-invariant systems (LTI). Impulse response. Stability and causality. Systems interconnection (series, parallel, feedback). Finite-difference equations as representation of LTI systems.
· Zeta transform. Definition and principal properties. Region of convergence. Analysis of LTI systems via Zeta transform. Transfer functions, poles and zeros. Frequency response. Stability condition in the Zeta domain
· FIR filters. Linear phase and LTI filter with symmetrical impulse response. FIR filters design with the window method.
· IIR filters. Design by poles and zeros placement. Design of digital IIR filters starting from their analog counterparts.
Warning: the class is taught in Italian. The course program is provided for reference only.
Professor(s)
Reception:
By appointment (email or phone)
Dipartimento di Informatica, via Celoria 18, stanza 6004 (6 piano, ala Ovest), Milano or remotely via Microsoft Teams