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Risorse bibliografiche
Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2017/2018
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 088966 - MULTIMEDIA SIGNAL PROCESSING
  • 089836 - MULTIMEDIA SIGNAL PROCESSING 1ST MODULE
Docente Marcon Marco
Cfu 5.00 Tipo insegnamento Modulo Di Corso Strutturato

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - MI (474) TELECOMMUNICATION ENGINEERING - INGEGNERIA DELLE TELECOMUNICAZIONI*AZZZZ088966 - MULTIMEDIA SIGNAL PROCESSING
Ing Ind - Inf (Mag.)(ord. 270) - MI (481) COMPUTER SCIENCE AND ENGINEERING - INGEGNERIA INFORMATICA*AZZZZ088966 - MULTIMEDIA SIGNAL PROCESSING
099325 - FUNDAMENTALS OF MULTIMEDIA SIGNAL PROCESSING

Programma dettagliato e risultati di apprendimento attesi

This module covers the fundamental tools for digital signal processing. In particular it addresses topics of signal analysis and filtering concerning audio and video data.

Some aspects of Statistical Signal Processing will also be presented during the course.

Participants will learn basic tools for digital signal filtering and analysis acquiring the knowledge to design specific filters and . In particular the program will be articulated in the following parts:

 

Review of Analog Signal Processing theory:

Some fundamentals of Analog Signal Processing will be recalled (sampling, quantization, Fourier Transform and Series, noise description...).

Introduction to Discrete Signals Transforms:

The z-transform, the Discrete Time Fourier Transform and the Discrete Fourier Transform will be described with their properties and application to filter design and analysis.

Introduction to Digital Filters:

This course part will cover Time-domain filter representations, transfer function analysis, frequency response analysis, Finite and Infinite impulse response implementation; stability analysis.

Windowing and Short Time Fourier Transform:

Overview of windows and real-time processing; overlap and add, overlap and save,  Short Time Fourier Transform for real time processing

Introduction to Multirate Processing:

Downsampling, upsampling, polyphase filters, perfect reconstruction filter banks.

Elements of Statistical Signal Processing:

Random sequences, properties and characterization. Spectral estimation, the Periodogram, linear prediction. Introduction to estimation theory, power spectral density, parametric and nonparametric spectral estimation. Autocorrelation and autocovariance methods.

 

Laboratory activities

Laboratory activities enable student to improve their understanding of the concepts learnt during the lectures.

The proposed examples of applications and exercises, cover audio, image and video processing, and are based on Matlab® and the related toolboxes (Digital Signal Processing System Toolbox, Audio System Toolbox, Image acquisition toolbox, Image Processing Toolbox ).

Examples of real-time processing with embedded devices (Raspberry Pi) and Simulink will also be provided.


Note Sulla Modalità di valutazione

The exam for this module is a written test with 3 or 4 exercises to be solved in 2 hours. Two or three exercises require a numerical/procedural solution while the last one is a exercise requiring the definition of a Matlab procedure in order to solve the question and will focus on exercises exposed during laboratories. The Matlab code has to be written directly on the paper without any computer aid.
The exam for the first module will take place only in the written version; no oral exams, integrations or projects will be considered in order to increase the obtained grade.
In order to pass the whole Multimedia Signal Processing exam (first and second module) (for students that are not following just the first module ("Fundamentals of Multimedia Signal Processing")) a positive grade must be obtained in both modules and the final mark will be the average of the two marks rounded up the next integer.
In evaluating the average between the two modules a 30 cum laude mark in a module will be considered as 30; in order to get 30 cum laude as a final mark, the mark of at least one module must be 30 cum laude.
In every exam date one module will take place in the morning while the other in the afternoon (the sequence will be published in the web poliself) but the exams of both modules will take place in the same day; anyway you can choose to take on a single module or both modules in the same day.
Once you get a positive mark in a module this mark will be automatically frozen until you take again the same module in a following session; taking again the exam on the same module means that you register, participate and turn in your solution; if you simply participate to an exam but do not turn in your solution, this will not change your previous mark and you will be considered as "asbsentee".
Once you will get a positive mark in both modules the final mark will be evaluated and then published for the publishing period on the web poliself ; at the end of this period it will be automatically recorded. If you do not want to record that final grade you have to refuse it from the poliself: in that case both marks will be restored in a "frozen" state in order to allow you to take on again a module (or both of them). Anyway if you have a frozen mark in both modules at the end of each exam to which you signed in, the final average mark will be automatically published and, after the publishing period, automatically recorded: so, if you want to improve your final mark you have to remember to refuse the published final grade.


Bibliografia
Risorsa bibliografica facoltativaPaulo S. R. Diniz, Eduardo A. B. da Silva, Sergio L. Netto, Digital Signal Processing: System Analysis and Design. Second edition, Anno edizione: 2010, ISBN: 978-0521887755
Risorsa bibliografica facoltativaDAFX: Digital Audio Effects, 2nd Edition, Editore: Udo Zolzer, Anno edizione: 2011, ISBN: 9780470979679

Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
lezione
30.0
esercitazione
20.0
laboratorio informatico
0.0
laboratorio sperimentale
0.0
progetto
0.0
laboratorio di progetto
0.0

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
schedaincarico v. 1.6.2 / 1.6.2
Area Servizi ICT
04/06/2020