Digital Signal Processing

Credits
6
Types
Specialization complementary (Computer Engineering)
Requirements
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.

There are no exams in this subject. Assessment is based on laboratory activities, and teamwork reports.

Teachers

Person in charge

Weekly hours

Theory
1.5
Problems
0.5
Laboratory
2
Guided learning
0
Autonomous learning
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
      - Applications. Equalization, filtering and audio, image and video compression.
      - Discrete Fourier Transform (DFT).
      - Fast Fourier Transform (FFT).
      - Inverse Fourier Transform
    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


    Topic 1. What is Digital Signal Processing

    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: - Signals, systems and signal processing. - Applications of PDS - Basic operators in PDS - Architecture of DSP microprocessors - Structure of PDS systems
    • Problems: --
    • Laboratory: --
    • Guided learning: --
    • Autonomous learning: --
    Objectives: 4 24
    Contents:
    Theory
    2h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    3h

    Topic 2. Discretization of signals

    Actively participate in the face-to-face session. Independent study of the proposed materials. Resolution of the proposed problems.
    • Theory: Signal sampling. Sampled sinusoid. - Sampling theorem. - Spectrum of the sampled signals. - Continuous-discrete frequency ratio. - Analog to digital conversion. Quantifications. - Digital to analog conversion. reconstruction
    Objectives: 3 1 5 6
    Contents:
    Theory
    3h
    Problems
    0.5h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    8h

    Topic 3. Frequency analysis of the signal. Fourier transform

    Actively participate in face-to-face sessions. Independent study of the proposed materials. Resolution of the proposed problems. Search for information regarding the different discrete transforms: concept, properties, implementation and application in the PDS.
    • Theory: - Applications. Equalization, filtering and compression of audio, images and video. -Discrete Fourier transform (DFT). - Fast algorithm (FFT). - Inverse Fourier transform - Other discrete transforms (DCT, Wavelet
    Objectives: 4 7 8 9 20 21 22
    Contents:
    Theory
    3h
    Problems
    1h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    6h

    Topic 4. Z transform. Use for signal processing

    Actively participate in face-to-face sessions. Independent study of the proposed materials. Resolution of the proposed problems
    • Theory: - Transform Z. - Transform Inverse Z. - Properties of the transform Z. - Applications of the transform Z in the PDS
    Objectives: 10 11
    Contents:
    Theory
    3h
    Problems
    1h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    12h

    Topic 5. FIR digital filters

    Actively participate in the face-to-face session. Independent study of the proposed materials. Resolution of the proposed problems
    • Theory: - Introduction ¿ Average filters. - Ideal frequency response. - Windowing - Design of finite impulse response filters - Examples
    Objectives: 12 25
    Contents:
    Theory
    4h
    Problems
    2h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    12h

    Topic 6. IIR digital filters

    Actively participate in face-to-face sessions. Independent study of the proposed materials. Resolution of the proposed problems
    • Theory: - Introduction - Design of infinite impulse response filters - Poles and zeros method - Examples
    Objectives: 7 13 14 15
    Contents:
    Theory
    4h
    Problems
    2h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    12h

    Topic 7. Audio processing

    Actively participate in face-to-face sessions. Independent study of the proposed materials. Resolution of the proposed problems
    • Theory: Equalization Sound Effects Compression Sound and Voice Synthesizer
    Objectives: 4 24 2 16 17 18 20 21
    Contents:
    Theory
    3.5h
    Problems
    1h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    9h

    Practice 1. Systems and signals

    Comprehensive reading of the statement of the practice, and of the rest of the materials indicated in the statement. Carrying out the previous activities indicated in the statement. Completion of the exercises that must be handed in at the beginning of the laboratory session.
    Objectives: 4 24 2 3 1 5 6 17 18 20
    Contents:
    Theory
    0h
    Problems
    0h
    Laboratory
    6h
    Guided learning
    0h
    Autonomous learning
    4h

    Practice 2. Sampling

    Comprehensive reading of the statement of the practice, and of the rest of the materials indicated in the statement. Carrying out the previous activities indicated in the statement. Completion of the exercises that must be handed in at the beginning of the laboratory session.
    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

    Practice 3. DSP processor

    Comprehensive reading of the statement of the practice, and of the rest of the materials indicated in the statement. Carrying out the previous activities indicated in the statement. Completion of the exercises that must be handed in at the beginning of the laboratory session.
    Objectives: 4 2 3 1 13 14 15 19
    Contents:
    Theory
    0h
    Problems
    0h
    Laboratory
    6h
    Guided learning
    0h
    Autonomous learning
    4h

    Practice 4. FIR Filters with DSP

    Comprehensive reading of the statement of the practice, and of the rest of the materials indicated in the statement. Carrying out the previous activities indicated in the statement. Completion of the exercises that must be handed in at the beginning of the laboratory session.
    Objectives: 16 17 18 19 20 23
    Contents:
    Theory
    0h
    Problems
    0h
    Laboratory
    6h
    Guided learning
    0h
    Autonomous learning
    6h

    Practice 5. IIR Filters with DSP

    Comprehensive reading of the statement of the practice, and of the rest of the materials indicated in the statement. Carrying out the previous activities indicated in the statement.
    Objectives: 17 19 21 22 23
    Contents:
    Theory
    0h
    Problems
    0h
    Laboratory
    6h
    Guided learning
    0h
    Autonomous learning
    8h

    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.

    Evaluation methodology

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

    NT is obtained from a teamwork project which has a weight of 90% 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 NL laboratory mark is obtained from the average of the individual evaluations of the practices There will be 5 evaluable practices during the course.

    Bibliography

    Basic

    Complementary

    Previous capacities

    Programming in language C.
    To know how numbers are represented on a computer, and know how to perform arithmetic-logical operations.
    To know the operation and structure of the processor.
    To know the architecture and operation of a computer.
    To understand written documentation in English correctly.