Advanced Topics on Signal Processing

Code:

MAP-T031

Acronym:

TAPS

Keywords
Classification	Keyword
OFICIAL	Telecommunications Engineering

Instance: 2024/2025 - 1S

Active?	Yes
Web Page:	https://moodle2425.up.pt/course/view.php?id=4033
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Doctoral Program in Telecommunications

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MAP-T	2	Syllabus since 2022/23	1	-	6	56	162

Teaching language

Portuguese and english

Objectives

This course aims to motivate students to fundamental and advanced signal processing concepts and techniques in the areas of spectrum estimation, adaptive filtering, sonar, radar, and synthetic aperture systems.

Learning outcomes and competences

The objective is to empower students with analysis and design skills in a variety of technologies and application areas including robust signal modeling, estimation, detection, and communication, as well as robust monitoring and detection of signals, objects, and environmental conditions.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Basic knowledge of signal processing concepts and techniques.

Program

1. Background Review





2. Spectrum Estimation






3. Adaptive filtering






4. The matched filter





5. Signal processing in sonar/radar






6. Signal processing in synthetic aperture systems

Mandatory literature

Dimitris G. Manolakis, Vinay K. Ingle, Stephen M. Kogon; Statistical and adaptive signal processing, Artech House, 2005. ISBN: 1580533663
Mark Richards, James Scheer, William Holm; Principles of Modern Radar – Vol. I: Basic Principles, SciTech Publishing, 2010. ISBN: 978-1-891121-52-4
Simon Haykin; Adaptive filter theory. ISBN: 0-13-322760-X

Teaching methods and learning activities

The topics of the curricular unit will be explained and discussed in lectures (one 3-hour class per week) where applied exercises and case studies illustrating the techniques and technologies in focus and based on signal processing will be addressed. These exercises and case studies will also be the object of specific home assignments that will contribute to assessment. Relevant teaching materials will be made available to students on the Moodle platform.

Software

Matlab

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Participação presencial	10,00
Teste	30,00
Trabalho prático ou de projeto	60,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	70,00
Frequência das aulas	56,00
Trabalho de campo	16,00
Trabalho escrito	20,00
Total:	162,00

Eligibility for exams

Attendance in the curricular unit is recognized for students who do not exceed the limit of absences (established in the FEUP General Evaluation Rules) and who have participated in at least 70% of the assessment moments/elements specified throughout the semester.

Calculation formula of final grade

The final grade will be obtained by averaging the grades obtained in mini-tests, specific homework assignments, and/or mini-projects to be developed in groups of students throughout the semester.