2023
Signals and Systems
Name: Signals and Systems
Code: EME13043M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Electrotechnical Engineering
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Regime de Frequência: Presencial
Sustainable Development Goals
Learning Goals
Obtain knowledge in the area of discrete systems and their applications. Understand the advantages and limitations of digital signal processing systems. Know how to develop digital signal processing programs, design filters and perform spectral analysis.
Contents
1. Introduction to signal processing
Signal characterization and classification. Typical operations in signal processing. Signal examples.
2. Discrete time systems and signals
Sampling. Discrete time systems. Characterization of linear and time invariant systems. Signal correlation.
3. Sampling of continuous signals
Sampling theorem. Aliasing problem. Signal reconstruction. Interpolation and decimation.
4. Z transform
Properties. Convolution. Transfer function of a discrete system. Stability and causality.
5. Discrete Fourier Transform (DFT)
DFT definition and its inverse. DFT computation of real sequences. Convolution using the DFT. Spectral leakage and temporal windows. FFT (Fast Fourier Transform).
6. Digital Filters
FIR (Finite Impulse Response) and IIR (Infinite Impulse Response) filters. Design of FIR type filters. Design of IIR type filters.
Signal characterization and classification. Typical operations in signal processing. Signal examples.
2. Discrete time systems and signals
Sampling. Discrete time systems. Characterization of linear and time invariant systems. Signal correlation.
3. Sampling of continuous signals
Sampling theorem. Aliasing problem. Signal reconstruction. Interpolation and decimation.
4. Z transform
Properties. Convolution. Transfer function of a discrete system. Stability and causality.
5. Discrete Fourier Transform (DFT)
DFT definition and its inverse. DFT computation of real sequences. Convolution using the DFT. Spectral leakage and temporal windows. FFT (Fast Fourier Transform).
6. Digital Filters
FIR (Finite Impulse Response) and IIR (Infinite Impulse Response) filters. Design of FIR type filters. Design of IIR type filters.
Teaching Methods
The theoretical-practical classes are used to present the theory and solve problems that help consolidate the presented concepts. Programs for digital processing of several signals will be developed in the laboratory classes, including the use of DFT for spectral analysis of signals. Design of digital filters and their implementation will also be performed in the laboratory classes. Programming of the signal processing algorithms will be executed in Matlab and C.
The assesment consists of 2 projects P1 and P2 presented in the form of articles following the template of a scientific publication.
The works P1 and P2 will be noticed in the interval [0.20].
The work can be done by groups of 2 people max or individual.
The final grade NF will be the result of the average grade of the two works P1 and P2, being necessary the approval in both works.
NF = (P1 + P2) / 2
If NF> = 9.5 approved
If NF = 9,5 : Approved
If NF< 9,5 : Failed.
The assesment consists of 2 projects P1 and P2 presented in the form of articles following the template of a scientific publication.
The works P1 and P2 will be noticed in the interval [0.20].
The work can be done by groups of 2 people max or individual.
The final grade NF will be the result of the average grade of the two works P1 and P2, being necessary the approval in both works.
NF = (P1 + P2) / 2
If NF> = 9.5 approved
If NF = 9,5 : Approved
If NF< 9,5 : Failed.
Teaching Staff
- Frederico José Lapa Grilo [responsible]
