Course Descriptions

Course Credits / Total Class Hours Description Type
SCIENTIFIC METHODOLOGY

Code: ESE410019

3 / 45
Science, ethics and society. Research on Graduate level. Research documentation. Research topic: problem formulation and research hypotheses, objectives, theoretical references. Methodological procedures: collection, validation, analysis and discussion of data and results. The research project. Planning and structure of the final paper. Preparation of articles and theses. Required for all lines of research
EMBEDDED SYSTEMS DESIGN

Code: ESE410032

3 / 45 Specification and models, Embedded Systems Hardware, System Software, Embedded Systems Application. Required in the Embedded Systems research line
APPLIED POWER ELECTRONICS

Code: ESE410007

3 / 45 Sustainable and renewable energy. High-efficiency, high step-up DC-DC converters. Grid-connected DC – AC converters. Maximum power point tracking techniques. Reversibility in electric current and tension. Power factor correction in PMW rectifiers. PMW modulation techniques applied to converters. Required in the Power Electronics Systems research line
INTRODUCTION TO MACHINE LEARNING

Code: ESE410035

3 / 45 Introduction and overview of Machine Learning and its learning paradigms. Data pre-processing. Supervised learning (decision trees, instance-based and artificial neural networks). Unsupervised learning (data clustering). Evaluation measures. Selected topics (e.g. regression analysis, outlier detection, reinforcement learning). Required in the Applied Artificial Intelligence research line
SIGNALS AND DYNAMIC SYSTEMS ANALYSIS

Code: ESE410010

3 / 45 Signals and systems theory review . Random signals: random variables and random variable functions. Stochastic processes. Discrete and continuous-time signal processing: filtering, sampling and reconstruction. Mathematical analysis of linear systems: linear space, controllability, observability and stability. Nonlinear systems: dynamic behavior, phase plane analysis and stability. Linearization. Required in the Modeling and Control Systems research line
TEACHING PRACTICUM

Codes: ESE410027 to ESE410029

up to 3 / 45 Higher education teaching practice with the support of a supervisor. Required for scholarship holders only. Required for scholarship holders
ELECTROMAGNETIC COMPATIBILITY

Code: ESE410004

3 / 45 Advanced aspects of electromagnetic compatibility. Conducted and radiated emissions. Conducted and radiated susceptibility. Electromagnetic interference. Control of electromagnetic interference. Radiation and Coupling. Nonlinearity of electronic components. Signals spectrum. Parasitic elements of components. Crosstalk, filters and shielding. Standards. Projects for electromagnetic compatibility (printed circuit boards, signal integrity, earthing system, filters and logic disposition). Elective
MODELING AND CONTROL OF STATIC CONVERTERS

Code: ESE410008

3 / 45 Acquisition of dynamic static converter models. Average-value modeling. Small-signal analysis. The PWM switch model. Canonical circuit models. Modeling of Space-state models. State feedback. Nonlinear control systems. Elective
CONTROL SYSTEMS

Code: ESE410003

3 / 45 Fundamentals of classical control theory. Feedforward, cascade and prefiltering control. Performance and sensibility specifications of control systems.. Design of state-space control systems: pole allocation, observers, and linear quadratic optimal control. Robustness and robust control fundamentals. On-off and sliding mode controllers. Elective
EMBEDDED SYSTEMS - INSTRUMENTATION AND CONNECTIVITY

Code: ESE410033

3 / 45 Standard interfaces, amplifiers, filters, converters, power considerations and interface project. Elective
SOFTWARE ARCHITECTURE AND DESIGN PATTERNS

Code: ESE410036

3 / 45 Introduction to embedded software architecture. Software design patterns. Software architectures in embedded systems. Architecture evaluation methods. Case studies. Elective
TESTING AND VERIFICATION OF EMBEDDED SYSTEMS

Code: ESE410037

3 / 45 Importance of testing, types of testing and faults in embedded systems. Testing and verification of embedded systems software: techniques and methods. Case studies. Elective
STATISTICS FOR DATA ANALYSIS

Code: ESE410034

3 / 45 Descriptive statistics. Simple and multiple linear regression. Correlation. Monte Carlo method. Parameter estimation. Hypothesis testing. Testing the adequacy of a fit. Bayes' theorem. ANOVA. Factorial designs. Metrological aspects of experiments. Examples of applications in electronic systems. Elective
DATA SCIENCE

Code: ESE410031

3 / 45 Data Science Concepts. ETL (Extract, Transform and Load). Data mining and knowledge discovery. Exploratory data analysis. Application of machine learning models and algorithms. Data visualization. Concepts of Business Intelligence/Data Warehouse/Data Marts. Elective
INTRODUCTION TO OPTIMIZATION PROCESSES USING AI TECHNIQUES

Code: ESE410030

3 / 45 Introduction to the optimization process. Mathematical modeling of problems. Classification of existing problems. Main techniques for solving optimization problems. Generating initial solutions. Concept of dominance of solutions. Analysis of results. Case studies. Elective
SPECIAL TOPICS I – VI

Codes: ESE410020 to ESE410025

3 / 45 Course with variable content according to the availability and/or needs of the program. Elective
GUIDED STUDY IN ELECTRONIC SYSTEMS

Code: ESE410014

3 / 45 Individual study, or in a group of at most three students, of topics not covered by the regular courses and, according to the advisor, necessary for the development of the thesis. Elective