Digital Data Analysis

course ID

0023, 0024





14 Weeks

Semester DD


Course details

Section I: the transforms

Signal Processing I: sampling of the signal (the sampling theorem, the convolution, the correlation, correlation is not causation, decomposition of the signal on the sphere).

Signal Processing II: the Fourier transform (the DFT, the FFT, the power spectrum, the phases, discretization of the signal on the sphere).

The Information: Wavelets, PCA and EMD (data compression, MP3, JPEG2000,JP3D).

Section II: the signal and the noise

The Noise: noise sources, noise types and spectra, SNR maximization, noise suppression.

Data Restoring: image reconstruction vs scanning, speckle imaging, blind deconvolution.

Data Analysis: patterns in data, punctual operatore and filters, more transforms, morphological operators and descriptors.

In the LAB:

Data Access: FITS + multiFITS.

Datafication examples: H-R diagram, Kepler data and star periods.

The Fourier Transform: Fourier spectrum, digital filters, data manipulation (shifts, transform).

Data-cubes Analysis: Wavelet Spectra, EMD analysis.

Data Compression: image quality estimators, image information estimators.


Co-teaching: Dott. De Gasperis Giancarlo


The aim of the course is to provide to the student a broad overview of the various methods and techniques of data analysis, with a deeper insight on those used in modern-time astrophysics. In particular, we will study the aspects of digital information access, handling, restoration, manipulation, compression and transformation into data.