Digital Signal Processing

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Credits
6
Types
Specialization complementary (Computer Engineering)
Requirements
  • Prerequisite: CI
Department
ESAII
The subject “Digital Signal Processing aims to teach the student in the basic tools and techniques of digital signal processing and the hardware necessary for the implementation of these systems. A digital signal processor, or DSP, is a system based on a processor or microprocessor that has an instruction set, hardware and software optimized for applications that require very high speed numerical operations. The most common applications of a DSP are those that require real time processing, such as video and audio processing, instrumentation, communications, medical diagnostic equipment, mobile devices, digital TV, synthesis/recognition of voice, M3, etc.

Subject assessment is based on partial control, laboratory activities, and teamwork reports, being able to pass the subject without taking a final exam.

Teachers

Person in charge

  • Antoni Grau Saldes ( )

Weekly hours

Theory
1.3
Problems
0.7
Laboratory
2
Guided learning
0.4
Autonomous learning
5.6

Competences

Technical Competences

Common technical competencies

  • CT1 - To demonstrate knowledge and comprehension of essential facts, concepts, principles and theories related to informatics and their disciplines of reference.
    • CT1.1B - To demonstrate knowledge and comprehension about the fundamentals of computer usage and programming. Knowledge about the structure, operation and interconnection of computer systems, and about the fundamentals of its programming.
    • CT1.2A - To interpret, select and value concepts, theories, uses and technological developments related to computer science and its application derived from the needed fundamentals of mathematics, statistics and physics. Capacity to solve the mathematical problems presented in engineering. Talent to apply the knowledge about: algebra, differential and integral calculus and numeric methods; statistics and optimization.
    • CT1.2B - To interpret, select and value concepts, theories, uses and technological developments related to computer science and its application derived from the needed fundamentals of mathematics, statistics and physics. Capacity to understand and dominate the physical and technological fundamentals of computer science: electromagnetism, waves, circuit theory, electronics and photonics and its application to solve engineering problems.
    • CT1.2C - To use properly theories, procedures and tools in the professional development of the informatics engineering in all its fields (specification, design, implementation, deployment and products evaluation) demonstrating the comprehension of the adopted compromises in the design decisions.
  • CT2 - To use properly theories, procedures and tools in the professional development of the informatics engineering in all its fields (specification, design, implementation, deployment and products evaluation) demonstrating the comprehension of the adopted compromises in the design decisions.
    • CT2.3 - To design, develop, select and evaluate computer applications, systems and services and, at the same time, ensure its reliability, security and quality in function of ethical principles and the current legislation and normative.
  • CT5 - To analyse, design, build and maintain applications in a robust, secure and efficient way, choosing the most adequate paradigm and programming languages.
    • CT5.5 - To use the tools of a software development environment to create and develop applications.
    • CT5.6 - To demonstrate knowledge and capacity to apply the fundamental principles and basic techniques of parallel, concurrent, distributed and real-time programming.
  • CT6 - To demonstrate knowledge and comprehension about the internal operation of a computer and about the operation of communications between computers.
    • CT6.2 - To demonstrate knowledge, comprehension and capacity to evaluate the structure and architecture of computers, and the basic components that compound them.
  • CT7 - To evaluate and select hardware and software production platforms for executing applications and computer services.
    • CT7.2 - To evaluate hardware/software systems in function of a determined criteria of quality.

Transversal Competences

Information literacy

  • G6 [Avaluable] - To manage the acquisition, structuring, analysis and visualization of data and information of the field of the informatics engineering, and value in a critical way the results of this management.
    • G6.3 - To plan and use the necessary information for an academic essay (for example, the final project of the grade) using critical reflection about the used information resources. To manage information in a competent, independent and autonomous way. To evaluate the found information and identify its deficiencies.

Technical Competences of each Specialization

Computer engineering specialization

  • CEC1 - To design and build digital systems, including computers, systems based on microprocessors and communications systems.
    • CEC1.1 - To design a system based on microprocessor/microcontroller.
    • CEC1.2 - To design/configure an integrated circuit using the adequate software tools.
  • CEC2 - To analyse and evaluate computer architectures including parallel and distributed platforms, and develop and optimize software for these platforms.
    • CEC2.3 - To develop and analyse software for systems based on microprocessors and its interfaces with users and other devices.
  • CEC3 - To develop and analyse hardware and software for embedded and/or very low consumption systems.
    • CEC3.1 - To analyse, evaluate and select the most adequate hardware and software platform to support embedded and real-time applications.
    • CEC3.2 - To develop specific processors and embedded systems; to develop and optimize the software of these systems. 

Objectives

  1. Differentiate the different types of systems, and define their characteristics
    Related competences: G6.2, CT1.2B,
  2. Understand the specific characteristics of a DSP processor over a general purpose processor
    Related competences: CT6.2, CEC3.1, CT1.1B, CT1.2B,
  3. Differentiate the different types of signals, and define their characteristics
    Related competences: G6.2, CT1.2B,
  4. Understand the meaning and benefits of digital signal processing (PDS), and what are the most common areas of application
    Related competences: CEC3.2, CEC3.1, G6.2, CT1.1B, CT1.2B,
  5. Understand the basics of the analog-to-digital conversion process, the interface needed in a DSP system, and the inherent limitations of this process.
    Related competences: CEC3.2, CEC1.2, CT6.2, CEC3.1,
  6. Specify, analyze, and determine the basic parameters of an analog input or output interface (acquisition and reconstruction).
    Related competences: CEC1.1, CEC1.2, CEC3.1,
  7. Know and apply the duality of the time-frequency domain of the signal. Understand the relationships between the two domains
    Related competences: CT1.2A, CT1.2C, G6.3, CT1.2B,
  8. Master the various alternatives for the implementation of the Fourier transform by discrete signals
    Related competences: CEC2.3, CEC3.2, CT1.2A, CT1.2C, G6.3, CT7.2, CT5.6, CT1.2B,
  9. Recognize the usefulness of discrete transformations in the field of PDS, and know how to apply these techniques
    Related competences: CEC2.3, CEC3.2, CT1.2A, CT1.2C, G6.3, CT7.2, CT5.6, CT1.2B,
  10. Use the z-transform for the representation, analysis and design of signals and discrete systems
    Related competences: CT1.2A, CT1.2C, CT1.2B,
  11. Define the most common applications of the z transform in PDS systems
    Related competences: CEC2.3, CEC3.1, CT5.6, CT2.3,
  12. Know and be able to apply the correlation technique in the field of PDS
    Related competences: CEC2.3, CEC3.2, CT1.2A, CT1.2C, CEC3.1, CT1.2B, CT2.3,
  13. Know the areas of application of filters in DSP systems
    Related competences: CEC2.3, CEC3.2, CT1.2B,
  14. Design filters according to the requirements of the application
    Related competences: CEC1.2, CT6.2, CT5.5, CT1.2B,
  15. Know how to apply FIR filters and IIR filters according to the requirements of the application
    Related competences: CEC2.3, CT1.2A, CEC1.2, CT1.2B,
  16. Know the differences in the architecture of floating point and fixed point DSPs
    Related competences: CEC2.3, CEC3.2, CT1.2A, CT1.2C, CEC1.1, CT7.2, CEC3.1, CT5.5, CT5.6, CT1.1B, CT1.2B,
  17. Analitzar els errors inherents en els sistemes DSP deguts a la quantificació i la resolució finita
    Related competences: CEC2.3, CT7.2, CT6.2, CEC3.1, CT1.1B, CT1.2B,
  18. Know how to use DSP-based development environments for rapid prototype development
    Related competences: CT7.2, CEC3.1, CT5.5, CT2.3,
  19. Know how to use numerical computing packages for simulation, analysis and development of algorithms in the field of DSP
    Related competences: CT5.5, CT1.2B, CT2.3,
  20. Know how to apply DSP techniques in audio systems
    Related competences: CEC2.3, CEC3.2, G6.3, CEC1.1, CT7.2, CT5.5, CT2.3,
  21. Know how to apply DSP techniques in the field of imaging
    Related competences: CEC2.3, CEC3.2, G6.3, CEC1.1, CT7.2, CT5.5, CT2.3,
  22. Know how to apply DSP techniques in the field of video
    Related competences: CEC2.3, CEC3.2, G6.3, CT7.2, CT5.5, CT2.3,
  23. Apply information compression techniques (JPEG, MPEG, ...)
    Related competences: CEC3.2, G6.3, CT7.2, CEC3.1, CT5.6, CT2.3,
  24. Know the basic components of a digital signal processing system
    Related competences: CEC2.3, CEC1.1, CT6.2, CT2.3,
  25. Know and be able to apply the convolution technique in the field of PDS
    Related competences: CEC2.3, CEC3.2, CT1.2A, CT1.2C, CEC3.1, CT1.2B, CT2.3,

Contents

  1. Introduction
    - Senyals, sistemes i processat del senyal.
    - Aplicacions del PDS
    - Operadors bàsics en el PDS
    - Arquitectura dels microprocessadors DSP
    - Estructura dels sistemes PDS
  2. SIgnal discretization
    - Mostreig de senyals. Sinusoide mostrejada.
    - Teorema del mostreig.
    - Espectre dels senyals mostrejats.
    - Relació de freqüències continu-discret.
    - Conversió analògic a digital. Quantificacions.
    - Conversió digital a analògic. Reconstrucció.
  3. Fourier Transform
    - Aplicacions. Equalització, filtrat i compressió d' àudio, imatges i vídeo.
    -Transformada discreta de Fourier (DFT).
    - Algorisme ràpid (FFT).
    - Transformada Inversa de Fourier
    - Altres transformades discretes (DCT,Wavelet)

  4. Z-transform and signal processing
    - Transformada Z.
    - Transformada Inversa Z.
    - Propietats de la transformada Z.
    - Aplicacions de la transformada Z en el PDS
  5. Correlation and convolution

    - Correlació creuada i autocorrelació
    - Fast correlation.
    - Convolució. Circular. Deconvolució. Fast linear convolution.
    - Exemples d'aplicacions.
  6. Digital Filters
    - Introducció
    - Funció de transferència.
    - Resposta impulsional.
    - Estabilitat.
    - Resposta freqüencial.
    - Estructures.
    - Criteris i procediment pel disseny de filtres digitals
    - Disseny de filtres de resposta impulsional finita
    - Disseny de filtres de resposta impulsional infinita
    - Exemples
  7. Processors for signal processing

    - Arquitectura i tipus
    - Criteris de selecció.
    - Implementació dels algorismes en PDS de propòsit general.
    - PDS de propòsit específic.
    - Sistemes de desenvolupament pel PDS.
  8. Audio signal processing

    Equalització
    Efectes de so
    Compressió
    Sintetitzador de so i veu
  9. Image and video signal processing
    Formats d'imatges. Compressió
    Efectes d'imatge
    Equalització
    Compressió de vídeo

Activities

Activity Evaluation act


Partial Exam


Objectives: 4 24 2 3 1 5 6 7 8 9 10 11 12 25
Week: 8
Type: theory exam
Theory
2h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
10h

Laboratory Examination


Objectives: 4 24 7 8 11 12 25 14 16 17 18 19 20 21 22 23
Week: 15
Type: lab exam
Theory
0h
Problems
0h
Laboratory
2h
Guided learning
0h
Autonomous learning
6h

Final Exam


Objectives: 4 24 2 3 1 5 6 7 8 9 10 11 12 25 13 14 15 16 17 18 19 20 21 22 23
Week: 15 (Outside class hours)
Type: final exam
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
3h
Autonomous learning
16h

Development of Topic 1

Participate actively in the face-to-face session. Autonomous study of the proposed materials. Solving the proposed problems. Search for information and systems in which PDS is key.
  • Theory: --
  • Problems: --
  • Laboratory: --
  • Guided learning: --
  • Autonomous learning: --
Objectives: 4 24
Contents:
Theory
1.5h
Problems
0.5h
Laboratory
0h
Guided learning
0h
Autonomous learning
3h

Desenvolupament del Tema 2

Participar activament en la sessió presencial. Estudi autònom dels materials propossats. Resolució dels problemes proposats.
Objectives: 3 1 5 6
Contents:
Theory
1.4h
Problems
0.6h
Laboratory
0h
Guided learning
0h
Autonomous learning
2h

Desenvolupament Tema 3

Participar activament en les sessions presencials. Estudi autònom dels materials proposats. Resolució dels problemes proposats. Recerca d'informació respecte les diferents transformades discretes: concepte, propietats, implementació i aplicació en el PDS.
Objectives: 4 7 8 9 20 21 22
Contents:
Theory
3h
Problems
1h
Laboratory
0h
Guided learning
1h
Autonomous learning
4h

Desenvolupament Tema 4

Participar activament en les sessió presencial. Estudi autònom dels materials proposats. Resolució dels problemes proposats
Objectives: 10 11
Contents:
Theory
1.4h
Problems
0.6h
Laboratory
0h
Guided learning
0h
Autonomous learning
2h

Desenvolupament Tema 5

Participar activament en la sessió presencial. Estudi autònom dels materials proposats. Resolució dels problemes proposats
Objectives: 12 25
Contents:
Theory
1.4h
Problems
0.6h
Laboratory
0h
Guided learning
0h
Autonomous learning
2h

Desenvolupament Tema 6

Participar activament en les sessions presencials. Estudi autònom dels materials proposats. Resolució dels problemes proposats
Objectives: 7 13 14 15
Contents:
Theory
2.5h
Problems
1.5h
Laboratory
0h
Guided learning
0h
Autonomous learning
4h

Desenvolupament Tema 7

Participar activament en les sessions presencials. Estudi autònom dels materials proposats. Resolució dels problemes proposats
Objectives: 4 24 2 16 17 18 20 21
Contents:
Theory
2h
Problems
2h
Laboratory
0h
Guided learning
0h
Autonomous learning
3h

Desenvolupament Tema 8

Participar activament en les sessions presencials. Estudi autònom dels materials proposats. Resolució dels problemes proposats
Objectives: 4 24 17 18 19 20 23
Contents:
Theory
2h
Problems
2h
Laboratory
0h
Guided learning
1h
Autonomous learning
3h

Desenvolupament Tema 9

Participar activament en les sessions presencials. Estudi autònom dels materials proposats. Resolució dels problemes proposats
Objectives: 4 17 18 19 21 22 23
Contents:
Theory
2h
Problems
2h
Laboratory
0h
Guided learning
1.5h
Autonomous learning
4h

Pràctica 1

Lectura comprensiva de l'enunciat de la pràctica, i de la resta de materials indicats a l'enunciat. Realització de les activitats prèvies indicades a l'enunciat. Realització dels exercicis que s'han d'entregar a l'inici de la sessió de laboratori.
Objectives: 4 24 2 3 1 5 6 17 18 20
Contents:
Theory
0h
Problems
0h
Laboratory
6h
Guided learning
0h
Autonomous learning
4h

Pràctica 2

Lectura comprensiva de l'enunciat de la pràctica, i de la resta de materials indicats a l'enunciat. Realització de les activitats prèvies indicades a l'enunciat. Realització dels exercicis que s'han d'entregar a l'inici de la sessió de laboratori.
Objectives: 4 24 2 7 8 9 10 11 12 25 20
Contents:
Theory
0h
Problems
0h
Laboratory
6h
Guided learning
0h
Autonomous learning
6h

Pràctica 3

Lectura comprensiva de l'enunciat de la pràctica, i de la resta de materials indicats a l'enunciat. Realització de les activitats prèvies indicades a l'enunciat.
Objectives: 4 2 3 1 13 14 15 19
Contents:
Theory
0h
Problems
0h
Laboratory
4h
Guided learning
0h
Autonomous learning
4h

Pràctica 4

Lectura comprensiva de l'enunciat de la pràctica, i de la resta de materials indicats a l'enunciat. Realització de les activitats prèvies indicades a l'enunciat.
Objectives: 16 17 18 19 20 23
Contents:
Theory
0h
Problems
0h
Laboratory
4h
Guided learning
0h
Autonomous learning
6h

Pràctica 5

Lectura comprensiva de l'enunciat de la pràctica, i de la resta de materials indicats a l'enunciat. Realització de les activitats prèvies indicades a l'enunciat.
Objectives: 17 19 21 22 23
Contents:
Theory
0h
Problems
0h
Laboratory
6h
Guided learning
0h
Autonomous learning
8h

-

Realització s'un treball relacionat amb el contingut de l'assignatura, on s'ha de realitzar l'èmfasi en la part de recerca bibliogràfica. L'estudiant ha d'utilitzar bases de dades de recursos d'informació avançades, saber realitzar cerques en ella, i valorar críticament les referències localitzades.
Objectives: 4 24 2 3 1 5 6 7 8 9 10 11 12 25 13 14 15 16 17 18 19 20 21 22 23
Week: 15
Type: problems exam
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
0h

Teaching methodology

No distinction will be made between theory classes and problems, the theoretical classes will be reinforced with examples showing possible alternatives and solutions to problems in the field of DSP (both components of a DSP system and applications).
The lab sessions will be held 'in situ' in the teaching laboratory of the department at the FIB. It is an unavoidable requirement to have carried out a previous work that will be specified by each one of the practices. Therefore attendance to laboratory sessions is mandatory.

Evaluation methodology

The grade of the subject is obtained from two components: the theory / problem grade (NT) and the laboratory grade (NL). Both components weigh 50% of the final grade.

NT is obtained from a Partial Examination (EP), which has a weight of 30% in the NT, a Final Examination (EF), which has a weight of 60% in the NT, and the evaluation of activities directly related to transversal competence (ACT), which has a weight of 10% in the NT.

ACT is obtained from the realization of a work related to the content of the subject, where the student will look for information to complete the aspects worked. Special attention is paid to the quality of the references used, their obtaining and critical assessment, and their correct citation.

The grade obtained in EP can be recovered with EF, as the corresponding weight (30%) is applied on the maximum of the two grades.
NT = max (0.30 * EP + 0.6 * EF + 0.10 * ACT, 0.9 * EF + 0.10 * ACT)

The NL laboratory mark is obtained from the average of the individual evaluations of the practices (NL1) and the mark of a final examination of practices (NL2). There will be 5 evaluable practices during the course.

Bibliography

Basic:

Complementary:

Previous capacities

Programming in language C.
Programming in some assembly language.
Knowledge of the concept of electronic circuit, and electronic components.
Know how numbers are represented on a computer, and know how to perform arithmetic-logical operations.
Know the operation and structure of the processor.
Know the architecture and operation of a computer.
Understand written documentation in English correctly.Programación en lenguaje C.

Addendum

Contents

NO HI HA CANVIS RESPECTE LA INFORMACIÓ PUBLICADA A LA GUIA DOCENT

Teaching methodology

Totes les classes seran no presencials, tant les classes de teoria com els laboratoris

Evaluation methodology

No hi haurà examen, l'avaluació serà en funció de les pràctiques lliurables.

Contingency plan

Si es produïssin rebrots per la pandèmia, les classes seguirien el seu curs normal al ser no presencials, tant la teoria com els laboratoris.