Ing Ind - Inf (Mag.)(ord. 270) - MI (475) ELECTRICAL ENGINEERING - INGEGNERIA ELETTRICA

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093585 - MEASUREMENT ORIENTED DIGITAL SIGNAL PROCESSING

Obiettivi dell'insegnamento

This subject is aimed at providing students with the theoretical background of Digital Signal Processing (DSP) oriented to measurement applications. The sampling theory is covered, as well as the typical structure of measurement instruments based on DSP techniques. The main DSP algorithm are covered, such as the Fast Fourier Transform (FFT) and the digital filters with finite (FIR) and infinite (IIR) impulse response.

The course meets the requirements of the Dubliners Descriptors (DD), as reported in the next sections.

Risultati di apprendimento attesi

At the end of the course, the students are expected to gain skills in analyzing signals, both in the time domain and in the frequency domain, and are expected to identify the conditions under which a continuous-time signal can be sampled and converted into a discrete-time signal. (DD1)

The students are expected to understand and identify the possible errors that can be done in sampling signals, especially periodic signals and apply suitable techniques to mitigate them (DD1, DD2).

Students are also expected to master the fundametals of digital filtering, by designing and implementing simple FIR and IIR filters, with the support of computer design software (DD1, DD2).

At the end of the course, if all lab classes have been attended, the students are also expected to be capable of implementing simple digilat instruments, on a LabView platform, to process signals in the time and frequency domains (DD1, DD2).

Argomenti trattati

Topic #1: Theory of the discrete-time signals. Sequences. Discrete-time systems. Time and frequency-domain analysis of sequences. Fourier transform of a sequence.

Topic #2: Signal sampling. The sampling theorem. Periodic signal sampling. Spectral leakage. Methods for the mitigation of the spectral leakage errors.

Topic #3: Architecture of a DSP-based measuring instrument. Input stage and anti-aliasing filter. DSP stage.

Topic #4: Algorithms and methods of the spectral analysis of a signal. DFT algorithm. FFT algorithm.

Topic #5: Dynamical digital systems. Representation in the n domain.

Topic #6: The z transform. Definition and properties. Relationship with the Fourier transform. Region of convergency. Inverse z transform. Complex convolution theorem.

Topic #7: Dynamical digital systems. Representation in the z domain. Difference equation and transfer function. Relationship with the frequency response. Rational transfer functions. Representation in terms of poles and zeros.

Topic #8: FIR filters. Architecture and properties. Linear-phase FIR filters. FIR filter design.

Topic #9: IIR filters. Architecture and properties. IIR filter design starting from analog filters. Parameter sensitivity to the coefficient quantization.

Prerequisiti

The basic knowledge of function analysis is a fundamental and necessary prerequisite of this course. The students must master the concept of time and frequency domain and must know what a Fourier and Laplace transform are. The must be capable of recognizing the basic properties of a signal in the time and in the frequancy domains.

The students are supposed to know how to read and unedrstand mathematical equations including summations, derivatives and integrals.

The basic knowldege of metrology and the measurement uncertainty concept is also required.

Modalità di valutazione

The final test consists of a written test on the fundamental issues of the discrete-time signals and how to obtain them by sampling continuous-time signals (DD2). Passing the written test is the condition to access the oral test, that will cover all topics explained during classes and lab classes (DD2, DD4).

Bibliografia

Gabriele D'Antona e Alessandro Ferrero, Digital Signal Processing for Measurement Systems - Theory and Applications, Editore: Springer, Anno edizione: 2006, ISBN: 978-0357-24966-7

Software utilizzato

Nessun software richiesto

Forme didattiche

Tipo Forma Didattica

Ore di attività svolte in aula

(hh:mm)

Ore di studio autonome

(hh:mm)

Lezione

65:00

97:30

Esercitazione

35:00

52:30

Laboratorio Informatico

0:00

0:00

Laboratorio Sperimentale

0:00

0:00

Laboratorio Di Progetto

0:00

0:00

Totale

100:00

150:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione

Insegnamento erogato in lingua
Inglese

Disponibilità di materiale didattico/slides in lingua inglese

Disponibilità di libri di testo/bibliografia in lingua inglese

Possibilità di sostenere l'esame in lingua inglese

Disponibilità di supporto didattico in lingua inglese