Degree | Type | Year |
---|---|---|
2503758 Data Engineering | OB | 2 |
You can view this information at the end of this document.
There are no prerequisites. However, students should be familiar with the most basic concepts of fundamental linear algebra, mathematical analisys and probability theory.
To study the mathematical theory of information, for the discrete case, based on C.E. Shannon's papers in 1948. To study sources of data, source coding, data compression and channel coding. To study error-detecting and correcting codes for an efficient data transmission or data storage.
1.- Basic concepts. Discrete memoryless sources.
1.1.- The problems of communication.
1.2.- Measure of information.
1.3.- Shannon's model of discrete memoryless source.
1.4.- Entropy function.
1.5.- Mutual information.
1.6.- Discrete memoryless channels. Capacity.
2.- Source coding.
2.1.- Introduction and objectives.
2.2.- Constant length codes.
2.3.- Variable length codes. Unique decipherability.
2.4.- Shannon's bounds.
2.5.- Construction of optimal codes.
3.- Data compression.
3.1.- Types of compression. Measures of compression.
3.2.- Compression techniques.
3.3.- Statistical methods.
3.4.- Dictionary techniques.
3.5.- Compression of sound and images.
4.- Discrete memoryless channels.
4.1.- Models for channels.
4.2.- Calculation of channel capacity.
4.3.- Decoding rules.
4.4.- The fundamental theorem,
5.- Coding theory I: linear codes.
5.1.- Block codes. Minimum distance decoding.
5.2.- Introduction to finite fields.
5.3.- Linear codes. Generator matrices.
5.4.- Equivalent codes. Systematic encoding.
5.5.- Dual codes. Parity-check matrices.
5.6.- Decoding. Standard array and syndrome.
5.7.- Some families of important linear codes.
6.- Coding theory II: cyclic codes.
6.1.- Cyclic codes as ideals of polynomial rings.
6.2.- Generator and parity-check polynomials.
6.3.- Systematic encoding with cyclic codes.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Practice sessions | 12 | 0.48 | 1, 2, 3, 4, 5, 6 |
Problem sessions | 12 | 0.48 | 1, 2, 5 |
Theory lectures | 26 | 1.04 | 1, 2, 5 |
Type: Supervised | |||
Tutoring and consultations | 17 | 0.68 | 1, 2, 3, 5 |
Type: Autonomous | |||
Independent study | 25 | 1 | 1, 2, 3, 4, 5 |
Preparing exercices and practice | 25 | 1 | 1, 2, 3, 4, 5 |
Preparing the final test | 25 | 1 | 1, 2, 3, 5 |
Theoretical content will be taught through lectures, although students will be encouraged to actively participate in the resolution of examples. During problem sessions, a list of exercises will be resolved. Students are encouraged to solve the problems on their own in advance. Students will also be encouraged to present their own solutions in class. In the practical sessions, subjects related to the theoretical content of the course will be developed. Campus Virtual will be used for communication between lecturers and students (material, updates, announcements, etc.).
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Final test | 60% | 3 | 0.12 | 1, 2, 5 |
Practice | 25% | 2 | 0.08 | 1, 2, 3, 4, 5, 6 |
Tests based on exercise resolutions in exercise-base classes | 15% | 3 | 0.12 | 1, 2, 3, 5 |
Continuous-assessment dates will be published on Campus Virtual. Specific programming may change when necessary. Any such modification will always be communicated to students through Campus Virtual, which is the usual communication platform between lecturers and students.
Subject assessment (out of 10 points) will be carried out as follows:
For each of the individual partial tests a minimum qualification of 0.5 points is required. There are no other minimum qualifications in each part. In order to pass, the different parts must add up to at least 5 points. No single assessment is offered.
Notwithstanding other disciplinarymeasures deemed appropriate, and in accordance with the academic regulations in force, assessment activities will receive a zero whenever a student commits academic irregularities that may alter such assessment. Assessment activities graded in this way and by this procedure will not be re-assessable. Irregularities contemplated in thisprocedure include, among others: the total or partial copying of an evaluation activity; allowing others to copy; presenting group work that has not been done entirely by the members of the group; presenting any materials prepared by a third party as one’s own work, even if these materials are translations or adaptations, including work that is not original or exclusively that of the student; having communication devices (such as mobile phones, smart watches, etc.) accessible during theoretical-practical assessment tests (individual exams).
An overall grade of 5 or higher is required to pass the subject. A "non-assessable" grade cannot be assigned to students who have participated in any of the individual partial tests or the final exam. No special treatment will be given to students who have completed the course in the previous academic year, except that the practice grade previously obtained can be assigned to this course gradebook. In order to pass the course with honours, the final grade must be a 9.0 or higher. Because the number of students with this distinction cannot exceed 5% of the number of students enrolled in the course, this distinction will be awarded to whoever has the highest final grade.
In the case of exercise resolution, a review may be requested after the date of the activity. For all other assessment activities, a place, date and time of review will be indicated allowing students to review the activity with the lecturer. If students do not take part in this review, no further opportunity will be made available.
To consult the academic regulations approved by the Governing Council of the UAB, please follow this link:
http://webs2002.uab.es/afers_academics/info_ac/0041.htm
*L. Huguet i J. Rifà. Comunicación Digital. Ed. Masson, 1991.
*D. Salomon: Data compression - The Complete Reference, 4th Edition. Springer 2007.
*R.B. Ash. Information Theory. John Wiley and Sons Inc, 1965.
*G. Alvarez. Teoría matemática de la información. Ediciones ICE, 1981.
*T.C. Bell, J.G. Cleary i I.H. Witten. Text Compression. Prentice Hall, 1990.
*F.J. MacWilliams and N.J.A. Sloane. The theory of error-correcting codes. North-Holland, Amsterdam, 1977.
For practices it will be used SageMath. https://www.sagemath.org/ SageMath is an open source mathematical software system licensed under the GPL. It is based on different open source packages: NumPy, SciPy, matplotlib, Sympy, Maxima, GAP, FLINT, R and others. Its combined potential can be accessed through a common Python-based language or directly through interfaces. Since version 9.0 in January 2020, SageMath has been using Python 3.
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PAUL) Classroom practices | 811 | Catalan | second semester | morning-mixed |
(PAUL) Classroom practices | 812 | Catalan | second semester | morning-mixed |
(PLAB) Practical laboratories | 811 | Catalan | second semester | morning-mixed |
(PLAB) Practical laboratories | 812 | Catalan | second semester | morning-mixed |
(PLAB) Practical laboratories | 813 | Catalan | second semester | morning-mixed |
(TE) Theory | 81 | Catalan | second semester | morning-mixed |