Signal Processing

Recommended Prerequisites

Signals and Systems; Calculus I, II and III; Linear Algebra

Teaching Methods

The teaching methodology consists of theoretical-practical classes, where the main concepts, principles and fundamental theories regarding signal processing are taught. These classes also include solving exercises with practical applications, where the theoretical knowledge may be applied. With this approach, conditions exist for the development of competencies in problem solving and critical reasoning.

Learning Outcomes

To provide the students with the main concepts and principles of signals in discrete time. To understand the representation of discrete signals in the frequency domain. To understand the relationship between continuous time signals and their representation in discrete time, by performing sampling. To learn the main techniques of digital filters projects and use them in basic lab experiments.

Work Placement(s)

No

Syllabus

1. Discrete time Fourier series

2. Discrete time Fourier transform (DTFT)

3. Discrete Fourier transform (DFT)

4. Z-transform for discrete-time signals

5. Sampling of continuous-time and discrete-time signals

6. Digital filter projects – IIR and FIR

Head Lecturer(s)

Henrique José Almeida da Silva

Assessment Methods

Assessment
Evaluation consists of a final exam (100%) or, alternatively, 2 mid-term exams, promoting continuous learning (each with a 50% weight on the final mark).: 100.0%

Bibliography

Alan Oppenheim, Allan Willsky, Signal and Systems, Prentice Hall, 2nd edition, 1997.

Alan Oppenheim, Ronald Schafer, John Buck, Discrete-time Signal Processing, Prentice Hall, 2nd edition, 1999.

Sanjit K. Mitra, Digital Signal Processing: A Computer-Based Approach, McGraw-Hill, 3rd edition, 2005.