Subject: Digital Signal Processing
Number of ECTS:
1. - Skill development in the field of digital signal processing. Students will be learn how to use the techniques and tools of analysis and design in digital signal processing.
2. - Emphasis is placed on the acquisition of the fundamental concepts in DSP: review of the concepts already addressed in Signals and Systems, such as: signal sampling and reconstruction; analysis of signals in the discrete frequency domain and Z transform.
4. - Study of some of the practical applications of DFT: correlation studies and spectral analysis; multirate signal processing, decimation and interpolation. Of particular relevance is the use of analysis and simulation tools, namely in MATLAB environment, where exercises are performed, algorithms presented in the theoretical classes, providing the student with the solidification of the concepts.
3, - Techniques most relevant for synthesis of digital filters, different implementation architectures; the discrete Fourier transform and its properties and fast realizations.
1. - Revisions on the characterization and representation of discrete time signals and systems; the discrete time Fourier transform; the Z-transform, sampling, quantization and reconstruction of signals by interpolation.
2. - Basic discrete systems: inverse system, all-pass systems, minimum and maximum phase systems, linear and time invariant systems. Linear phase FIR systems. Spectral decomposition.
3. - Discrete IIR and FIR filters syntheis and their implementation.
4. - The Discrete Fourier Transform (DFT), properties and applications to spectral analysis and filter synthesis.
5. - Fast Fourier Transform (FFT) algorithms. Specific algorithms: Goertzel algorithm
6. - Application of FFT in fast FIR convolution, in correlation studies and spectral estimation
7. - Introduction to multirate processing, decimation and interpolation and filter banks.
Alam V. Oppenheim , 2009 , Digital Signal Processing , Prentice-Hall Signal Processing Series
Vinay K. Ingle , 2016 , Digital Signal Processing Using MATLAB : A Problem Solving Companion , Cengage Learning
Dimitris G. Manolakis , 2011 , Applied Digital Signal Processing , Cambridge University Press
Assesssment methods and criteria:
Classification Type: Quantitativa (0-20)
The teaching methodology is based on theoretical classes and theoretical-practical classes. In the theoretical classes will be the theoretical presentation and, when appropriate, the practical illustration of the contents of the curricular unit. In some of these classes are also presented class questions with impact on the classification of distributed evaluation. The theoretical-practical classes include two types of activity: assist the students in the resolution "in paper and pencils", or in Matlab environment of exercises proposed to consolidate the acquired toric concepts; in some theoretical-practical classes, experimental works are carried out using a real-time digital signal processing platform