Digital Data Processing
Period: Second semester
Course unit contents:
THEORETICAL CONCEPTS ABOUT DIGITAL DATA PROCESSING:
Sampling of a continuous signal: sampling frequency and resolution. Nyquist-Shannon sampling theorem.
Signal statistics: outlier detection and removal, detrend, offset removal. The Least-Square method. Signal-to-noise ratio.
Discrete-time Fourier transform: amplitude and phase spectra computation.
Convolution and digital filters, tapers.
Cross-correlation and autocorrelation: search for similarity between different signals, search for periodicity within a signal.
F-K spectra and filters.
The phase of the signal: periodic behaviour, phase unwrapping, phase shift versus phase rotation.
Frequency-time analysis.
MATLAB PROGRAMMING:
Matrices, vectors and scalars. Numerical formats. Scripts versus functions.
Operations between scalars, vectors and matrices. Mathematical and trigonometric functions. 1D plots.
Statistical operators.
Complex numbers, periodic functions, spectra computation and representation.
For versus while loops. Writing and reading files. 2D and 3D plots.
Convolution and cross-correlation.
Design of digital filters.
Phase unwrapping.
Spectrograms.
Planned learning activities and teaching methods: Class lectures. Practical exercises with MATLAB.