Digital Signal Processing and Analysis

Code:

M3002

Acronym:

M3002

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2021/2022 - 1S

Active?	Yes
Responsible unit:	Department of Mathematics
Course/CS Responsible:	Bachelor in Mathematics

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:B	0	Official Study Plan	3	-	6	56	162
L:CC	2	study plan from 2021/22	2	-	6	56	162
			3
L:F	0	Official Study Plan	2	-	6	56	162
			3
L:G	0	study plan from 2017/18	2	-	6	56	162
			3
L:IACD	2	study plan from 2021/22	3	-	6	56	162
L:M	41	Official Study Plan	2	-	6	56	162
			3
L:Q	2	study plan from 2016/17	3	-	6	56	162

Teaching language

Suitable for English-speaking students

Objectives

The course (UC) presents the main concepts and techniques of Signal Processing and Analysis, both from deterministic and stochastic point of views, with a special emphasis in the frequency domain.

The course focus on the understanding of concepts and methods, and its effective use in synthetic and experimental data analysis. The course makes an intensive use of advance computational tools (MATLAB).

Learning outcomes and competences

The course orientation emphasis is the understanding of the main concepts and methods, together with an effective use of the methods in synthetic and experimental data analysis. At the end of the semester, the students should be familiar with the fundamentals of  Digital Signal Processing, particularly the analysis in the frequency domain, and being able to:
1. Manipulate with ease the fundaments fundamentals of  signals and systems.
2. Know the properties and how to use the various transforms studied.
3. Describe the properties of a signal and a linear system  (in the time and frequency domain).
4. Describe and analyse the effect of sampling a signal, and the consequent implication in what regards real signals.
5. Implement FIR and IIR filters and analyse their effects in a critical way.
6. Use Matlab for the analysis of signals and systems.

Working method

Presencial

Program

1. Introduction to Digital Signal Processing and to the MATLAB software
2. Discrete time signals and systems
3. Fourier Series, Fourier Transform in continuos time and in discrete time
4. Signal and system analysis in the time and frequency domains.
5. Continuous time signals sampling, Discrete Fourier Transform (DFT)
6. Z Transform
7. Digital filters with Finite Impulse Response (FIR) and Infinite Impulse Response (IIR)
8. Spectral Analysis

Mandatory literature

000091830. ISBN: 007-124467-0
000039783. ISBN: 0-13-373762-4 (hardcover)
000039607. ISBN: 0-13-216771-9

Complementary Bibliography

000039124. ISBN: 0-02-318010-2
000016887

Teaching methods and learning activities

The classes are all of type TP (Theory / Practical). Some classes are used to present concepts and methods, illustrated with a variety of examples, and other classes are used to for the resolution of problems and the execution of small projects with MATLAB software, using real and simulated data.

Software

matlab

keywords

Technological sciences > Technology > Computer technology > Signal processing
Physical sciences > Mathematics > Applied mathematics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	60,00
Participação presencial	0,00
Trabalho laboratorial	40,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	56,00
Frequência das aulas	56,00
Trabalho laboratorial	50,00
Total:	162,00

Eligibility for exams

The course attendance has a compulsory component of practical assignments / mini-projects, with the submission of the corresponding functions / scripts / reports within the fixed schedules, and with a minimum classification of 8 (in a 0-20 scale).
The students might have to answer questions regarding the practical assignments made, during the lectures or in an oral exam.

Calculation formula of final grade

The course final mark will be based on the practical component (40% weight) and the final exam (60% weight), with both having to reach a minimum level of 8 (in a 0-20 scale).

Examinations or Special Assignments

n.a.

Special assessment (TE, DA, ...)

n.a.

Classification improvement

The practical component is not eligible for classification improvement.

Observations

Course Juri: Prof. André Marçal and Prof. Ana Paula Rocha