| Code |
14924
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| Year |
3
|
| Semester |
S1
|
| ECTS Credits |
6
|
| Workload |
PL(30H)/T(30H)
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| Scientific area |
Physics
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|
Entry requirements |
None
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Learning outcomes |
- To understand the characteristics of Continuous and Discrete Time Signals
- To understand the Continuous and Discrete Time Signals represented on the Frequency domain
- To design Analogue and Discrete Filters
- To process and analyse random signals
- To understand the Image Processing and Analysis techniques
- To understand the information classification and recognition models
- To understand the signal modulation and demodulation models.
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|
Syllabus |
1. Continuous and Discrete Signals (Signal Representation, Linear and Invariant Systems in Time, Temporal and Frequency Representation, Sampling)
2. Filters (Bode Diagrams, Continuous Signal Filters, Digital Signal Filters - IIR and FIR)
3. Random Signals (Random Signal Notion, Stochastic Signals, Ergodic Processes, Stationary Signals, Correlation and Power Spectrum Functions, Wiener and Kalman Filters)
4. Image Processing and Analysis (Image Acquisition and Representation, Spatial Convolution and Image Filtering, Two-dimensional Transforms, Spectral Image Analysis, Filtering, Two-dimensional FIR, Binary and Multilevel Image Morphology, Basic Image Analysis Techniques, Image Detectors Thresholds, Image Segmentation, Image Description, Wiener and Kalman Two-dimensional Estimator Filters)
5. Pattern Recognition (Signal and Image Characterization, Classification Techniques).
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Main Bibliography |
1. Haykin S and Van Veen B (2003). Signals and Systems, 2nd ed. Wiley
2. Hayes MH (1996). Statistical Digital Signal Processing and Modeling. Wiley
3. Pratt WK (2001). Digital Image Processing, 3rd ed. Wiley
4. Shapiro LG and Stockman GC (2001). Computer Vision. Prentice Hall
5. Proakis JG and Manolakis DG (1996). Digital Signal Processing: Principles, Algorithms, 4th ed. Prentice Hall
6.Oppenheim AV and Willsky AS (1997). Signals & Systems, 2nd ed. Prentice Hall
7. Woods JW (2006). Multidimensional Signal, Image and Video Processing and Coding. Academic Press
8. Duda RO, Hart PE and Stork DG (2000). Pattern Classification, 2nd ed. Wiley
9. Theodoridis S and Koutroumbas K (2009). Pattern Recognition, 4th ed. Academic Press
10. Girod B, Rabenstein R and Stenger A (2001). Signals and Systems. Wiley
11. Gray RM and Davisson LD (2004). Introduction to Statistical Signal Processing. Cambridge Univ. Press
12. Scharf L (1991). Statistical Signal Processing. Addison Wesley
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Teaching Methodologies and Assessment Criteria |
Practical Classes
- 3 projects:
- Continues time signal processing
- Discrete time signal processing
- Image Processing (MatLab)
Teorectical Classes supported with MatLab
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Language |
Portuguese. Tutorial support is available in English.
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