Subject: Analysis and Signal Processing

Scientific Area:

Electronics

Workload:

80 Hours

Number of ECTS:

7,5 ECTS

Language:

Portuguese

Overall objectives:

1 - Knowledge of signal processing techniques and understanding of how to apply them in systems analysis.
2 - Knowledge of the main operations on signals and transforms for manipulation in another domain.
3 - Understanding the sampling process of signals and the corresponding computation procedure.
4 - Understand how to analyze systems, using techniques for the time or frequency domain, particularly in the filter design.
5 - Use of Matlab software in signal analysis and processing.

Syllabus:

1 - Introduction to continuous and discrete signals and systems.
2 - Examples of signals and transformations. Random signals and noise. Signal correlation. Systems properties.
3 - Linear and time-invariant systems (LIT) and continuous and discrete convolution.
4 - Fourier series and spectrum concept.
5 - Fourier transform of continuous and discrete signals.
6 - Signal sampling and quantization. Discrete-time processing of continuous signals. Decimation and interpolation.
7 - Laplace transform, transfer function, SLIT described by differential equations, block diagrams and Bode diagrams.
8 - Z transform and difference equations.
9 - Introduction to filtering of continuous and discrete signals.

Literature/Sources:

C. L. Phillips, J. M. Parr e E. A. Riskin , 2003 , Signals, Systems and Transforms , Prentice Hall International
F. C. Velez Grilo, António, M. E. S. Casimiro, J. A. C. Lopes e J. A. R. Azevedo , 2010 , Teoria do Sinal e suas aplicações , Escolar Editora
A. V. Oppenheim e A. S. Willsky , 1997 , Signals and Systems , Prentice-Hall International
A.V. Oppenheim, R. W. Schafer , 2014 , Discrete-time signal processing , Pearson Education
B. Girod, R. Rabenstein, A.Stenger , 2001 , Signals and Systems, , John Wiley & Sons
D. G. Manolakis, V. K. Ingle , 2011 , Applied digital signal processing: theory and practice , Cambridge University Press

Assesssment methods and criteria:

Classification Type: Quantitativa (0-20)

Evaluation Methodology:
- Lectures; - Solving exercises; - Carrying out practical work in software. Evaluation: - Exams: 70%; - Practical work: 30%.