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Scheda Riassuntiva
Anno Accademico 2018/2019
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 (263) MUSIC AND ACOUSTIC ENGINEERING*AZZZZ088966 - MULTIMEDIA SIGNAL PROCESSING
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*AZZZZ099325 - FUNDAMENTALS OF MULTIMEDIA SIGNAL PROCESSING
088966 - MULTIMEDIA SIGNAL PROCESSING

Obiettivi dell'insegnamento

This course introduces the fundamental tools for digital signal processing. It mainly focuses on signal analysis and filtering concerning audio and video sources but the theoretical part allows the student to easily extend his/her knowledge to other digital signal processing fields.
The course aims at providing the participants with basic tools for digital signal filtering and analysis, and with the knowledge to design specific processing tools for 1D and 2D discrete signals.


Risultati di apprendimento attesi

Dublin Descriptors

Expected learning outcomes

Knowledge and understanding

Students will learn how to:

·        Move from the continuous to the discrete signals representation.

·        Deal with common discrete signal transforms (e.g. DTFT, DFT, Z transf., STFT) in 1D and 2D spaces.

·        Change sample rate of a discrete signal.

·        Deal with real-time digital signal processing and windowing.

·        Adopt multi-rate signal processing and design perfect reconstruction filter banks.

Applying knowledge and understanding

Given specific project cases, students will be able to:

·        Design the proper filter for a specific application.

Examples provided during the course will mainly focus on audio and video signals but the acquired theoretical background will allow the student to deal with digital filter design in other application fields.

·        Tune the system design in order to fulfill the specifications constraints in terms, e.g., of maximum delay, phase distortion or maximum filter length.

Lifelong learning skills

·        Students will learn how to design specific digital filters in order to fulfill project requirements and system constraints.

·        Students will learn how to analyze the behavior of digital filters both in time and in the frequency spaces.


Argomenti trattati

Main course Topics

  • 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 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 and space 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 and perfect reconstruction filter banks will be introduced.
  • Multimedia applications: practical filter design for audio signals, basic image processing (e.g. edge extraction, histogram processing,rescaling). 

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 ).


Prerequisiti

Students are required to know the basic principles of signal processing and to have basic programming skills.


Modalità di valutazione

The assessment will be based on a written exam at the end of the course. The written exam consists of numerical exercises, theoretical questions and programming exercises (in MatLab®); no further oral exams or projects are considered.

In particular, the assessment 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/theoretical 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 will take place only in the written version; no oral exams, integrations or projects will be considered in order to increase the obtained grade.

Assessment criterium for the whole Multimedia Signal Processing exam (1st and 2nd modules).

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.

Type of assessment

Description

Dublin descriptor

Written test

Solution of numerical problems

·        Filter design from project specifications.

·        Filter analysis and output calculation from a given input in time, space or frequency domains.

·        Procedures for signal trasformation: scaling, upsampling, downsampling

·        Multirate filter design

·        Windowing effect on different signals.

Exercises focusing on design aspects

·        Write Matlab® code to design a filter according to the specifications and process an assigned input.

·        Write Matlab® code to analyze a filter behaviour and process an assigned input.

·        Implement in Simulink ® a system for real time signal processing.

·        Write Matlab® code for signal transformation, features extraction.

·        Write Matlab® code for multirate signal processing, windowing and perfect reconstruction filters.

 

Theoretical questions on all course topics with open answer

1, 2

 

 

 

 

 

1, 2, 3

 

 

 

 

 

 

 

1, 4


Bibliografia

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
32:30
48:45
Esercitazione
17:30
26:15
Laboratorio Informatico
0:00
0:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
0:00
0:00
Totale 50:00 75:00

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
schedaincarico v. 1.6.1 / 1.6.1
Area Servizi ICT
08/12/2019