This subject is an elective course of the 4th year of the Informatics Engineering Degree in the speciality Computer Engineering (taught during the first four-month period).



The subject is intended to introduce the student of Computer Science to both the theoretical and practical aspects of Digital Signal Processing. Therefore, the subject uses concepts learned in previous subjects in the areas of mathematics (complex numbers, sinusoidal, etc.) and programming.



In the professional field, the subject enables students to process digitally any type of signal (sound, image, information from sensors, time series, etc.) in multiple fields (audio-visual, industry, medicine, meteorology, etc.). In this way, it serves as a link to other areas such as Data Science, Big Data, Industry 4.0, etc.



The fundamental objectives are:



- To introduce the student to the basic concepts related to Digital Processing: signals, systems, time and frequency analysis, filters.



- To deepen these concepts in the case of sound and image, and to show the methods used in digital systems to capture, process and produce this type of signals.



- To present practical applications of these techniques and alternatives for their implementation.



- To put into practice the concepts studied, applying them in the laboratory to real cases of sound (voice and music) and image processing, using MATLAB platform (other alternatives could be: SCILAB, Octave, Python…).

The learning outcomes provided by the subject are the following:



- Knowing how to use digital signal processing software and critically interpret the results obtained.



- Being able to apply the mechanisms of transformation of continuous signals to digital signals: sampling and quantification.



- Know the main methods of calculating the Fourier transform and know how to apply them to digital signals.



- Knowing the main parameters of FIR and IIR digital filters, and knowing how to design and apply them to digital signals.



- Develop a specific task with autonomy using self-management and self-regulation techniques.



- Communicate their ideas and arguments in an understandable way and according to the established formal criteria.



- Value teamwork, accepting the potential of diversity as a learning opportunity.



- Carry out their tasks responsibly in order to achieve the objectives and the collective result.

Theme 1

1.1 Introduction

1.2 Signals and systems Why digital processing?



Theme 2

2.1 Digital signals

2.2 Definitions and properties. Digitization. Basic signals and operations. Sound and image

2.3 Project. Introduction to a specific software for digital signal processing: Sound and Image



Theme 3

3.1 Time domain analysis

3.2 Usual operations. Windowing and short-term operations. Correlation

3.3 Projects. Time-domain analysis of sound and image signals



Theme 4

4.1 Frequency domain analysis

4.2 Starting idea. Fourier series and transform. Application to two-dimensional systems

4.3 Projects: Frequency analysis of sound and image signals



Theme 5

5.1 Filters.

5.2 LTI systems. FIR filters. Z transform. IIR filters. Non-linear filters.

5.3 Projects: Linear systems (FIR, IIR) and filter design.



Theme 6

6.1 Applications of digital signal processing.

6.2 Areas of application and examples.

6.3 Final projects: medium/high complexity projects in which acquired competencies

in the subject are applied.

There are four types of activities:



- Autonomous study by the students of the material available in the virtual classroom for each subject in which the theoretical/practical concepts to be used are presented, as well as a proposal of exercises associated with them. In addition to directly accessible information, students can use bibliographic references as support material.



- Presentation and exercise classes in which, in a participative way, the theoretical/practical concepts of each topic are shared and the doubts associated with them are clarified, always emphasizing their usefulness and practical aspects. In these sessions, the initially proposed exercises ("on paper") will be shared in order to deepen the theoretical foundations. Exercises will also be proposed on each topic that the students will have to solve and that will be evaluated with the corresponding feedback.



- Development of specific projects in which the students (preferably in groups of 2) apply the theoretical/practical concepts learned to real cases of sound (voice and music) and image processing, using MATLAB, SCILAB, Octave, etc. For each of these sessions, a technical report of results must be submitted that will be evaluated with the corresponding feedback.



- Development of a final project (medium/high complexity level) in which the students (preferably in groups of 2) will apply the theoretical/practical knowledge previously learned in the course.

In order to facilitate student learning, specific projects will be monitored by providing feedback based on previously established and shared evaluation criteria. In this way, students are aware of their level of learning and take steps to improve it if necessary.

• Continuous Assessment System
• Final Assessment System
• Tools and qualification percentages:
  • The percentages and types of assessment are specified in the following sections (%): 100

The assessment systems considered are the continuous assessment system and the final assessment system. In the ordinary call, the continuous assessment system is the one that will be used in preference, as indicated in the current regulations of the UPV/EHU. The mark is calculated as follows:



- Theory: classroom exercises and written tests 50%.

- Practice: specific projects 35% and final project 15%. There will be individual written evaluations that will weight the marks of the practical part.



For the final assessment mode, the students will have to submit the reports corresponding to the specific projects and the final project at least two weeks before the date of the ordinary call (date of the final theory test). In this case, the examination will weigh 60% and the practical part 40%. There will be an individual written evaluation that will weight the overall mark of the practical part.



In order to pass the subject, in any modality, it is necessary to pass both the practical and theoretical parts of the subject separately.



Students who, fulfilling the conditions to continue in the continuous assessment system, decide to opt for the final or global assessment, must inform the teacher responsible for the subject by email before the beginning of the second week of the grouped timetable of the four-month period established in the centre's calendar.

In the case of the extraordinary call, the final mark is calculated based on two parts:



- Theory (60%): Assessed by a knowledge test.



- Practical (40%): This is assessed on the basis of the technical reports corresponding to the specific and final projects, which must be submitted before the date of the theory test. There will be an individual written evaluation that will weight the overall mark of the practical part.



In order to pass the course it is necessary to pass both parts (theoretical and practical).

For the correct development of the subject it is required:

- a PC type personal computer.
- and specific software for signal processing (MATLAB, etc.), for the laboratory practices.

The centre provides both resources. In addition, students have the possibility of carrying out the practical projects on their own computers using the UPV/EHU's MATLAB corporate licence and free software (SCILAB, Octave, Python, etc.).

Basic bibliography

J. G. Proakis, D.G. Manolakis: "Tratamiento digital de señales". Prentice-Hall, 1997.

J. G. Proakis, D.G. Manolakis: Digital Signal Processing: Principles, Algorithms, and Applications. 4th Edition, Pearson Education, Inc., New Delhi, 2007.

V. Oppenheim, R. W. Schafer: "Digital Signal Processing". Prentice-Hall, 1988.

R. C. Gonzalez, R. E. Woods: "Digital Image Processing". Addison-Wesley, 1993.

S. S. Soliman, M.D. Srinath: "Señales y Sistemas continuos y discretos", Prentice Hall, 1999.

S. S. Soliman, M.D. Srinath: "Continuous and Discrete Signals and Systems", Prentice Hall, 1998.

In-depth bibliography

E. Soria: "Tratamiento Digital de Señales: Problemas y ejercicios resueltos", Pearson Prentice Hall, 2003.
C. S. Burrus: "Ejercicios de tratamiento de señal utilizando MATLAB v4". Prentice-Hall, 1997.
B. Gold, N. Morgan: "Speech and audio Signal Processing: Processing and perception of speech and music", Wiley 2000.
J. R. Deller, J. G. Proakis: "Discrete-Time Processing of Speech Signals". MacMillan, 1993.

Journals

Digital Signal Processing (Elsevier)
Signal Processing (Elsevier)
IEEE Signal Processing Letters

Web addresses

www.mathworks.com
www.scilab.org
www.dsprelated.com
www.gnu.org/software/octave
www.scipy.org