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Theoretical classes with detailed presentation, using audiovisual means, of the concepts, principles and fundamental theories and solving of basic practical exercises to illustrate the practical interest of the subject and exemplify its application to real cases.
Laboratory classes in which students should apply theoretical concepts that were taught in order to consolidate the same.
It is intended that students acquire a strong training in statistical and deterministic processing of discrete-time signals. The skills obtained will allow developing modern applications and signaling processing algorithms in different areas of knowledge.
1. Multi-rate signal processing
2. Discrete-time stochastic processes
3. Power spectral estimation
4. Optimal filtering
Fernando Manuel dos Santos Perdigão
Assessment
- Laboratory work (min. 25%; max 50%); - Midterm exam (max 45%); - Exam (min 30%).: 100.0%
• Sanjit K. Mitra (2005) – Digital Signal Processing: A Computer-Based Approach (3rd Ed.), McGraw-Hill.
• Monson H. Hayes (1996) – Statistical Digital Signal Processing and Modeling, John Wiley.