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ENVIRONMENTAL DATA AND SIGNALS PROCESSING

Degree course Environmental Enginnering
Curriculum NUOVE TECNOLOGIE PER LA TUTELA DEL TERRITORIO E DELL’AMBIENTE
Learnings PS.LM35.IND012.2013-2014
Academic Year 2016/2017

Module: ENVIRONMENTAL SIGNALS PROCESSING

Degree course Environmental Enginnering
Curriculum NUOVE TECNOLOGIE PER LA TUTELA DEL TERRITORIO E DELL’AMBIENTE
Learnings PS.LM35.IND012.2013-2014
Academic Year 2016/2017
ECTS 9
Scientific Disciplinary Sector ING-IND/31
Year First year
Time unit Second semester
Class hours 72
Educational activity Related and integrative training activities

Single group

Professor FRANCESCO CARLO MORABITO
Objectives The course has the objective of initiating students to the analysis and synthesis of mono and two-dimensional signals with the help of statistical techniques and analytical- numerical implemented at the computer.
Programme This is a part of a two part course (the other teacher is prof. Mario Versaci)

Introduction to Signal Processing (CFU 2)

General information on signal processing, analog signals, sampling and AD and DA conversion, discrete-time signals (numerical), linear difference equations with constant coefficients, representation in the time domain and frequency, multi-dimensional random signals, order statistics higher than the second, stochastic processes, concepts of estimation theory, maximum likelihood method, estimates of the minimum mean square error, method of maximum a posteriori probability, elements of information theory, informational entropy, mutual information, negentropy, correntropia, method of maximum entropy estimation, optimization methods.
Representation of digital systems using graphs and block diagrams, basic network structures for FIR and IIR systems.

Soft Computing Algorithms (CFU 1)

Genetic and Evolutionary Algorithms: general and methods of use, reproduction operators of crossover and mutation, space research and Fitness Landscape.
Adaptive systems, estimation of the gradient, iterative methods, Hebbian learning, Kohonen networks and self-organizing, dynamic recurrent networks, Hopfield networks.
Pattern recognition: formulations, linear and non-linear classifiers, treatment of uncertainty, representative problems in different research areas.

Analisi Multirisoluzione e Multidimensionale (CFU 2)

Advanced algorithms for signal processing, time-series study, analysis in the frequency domain, Fourier transform, Short-Time Fourier Transform, signal analysis in the time-frequency domain, processing of non-stationary signals, signals and nonlinear systems, Continuous and Discrete Wavelet Transform, wavelet decomposition, practical applications of the Wavelet Transform, Principal Component Analysis (PCA), Independent Component Analysis (ICA), practical applications of PCA and ICA, time series and chaotic dynamics, elementary circuits chaotic.

Implementazione numerica degli algoritmi (CFU 1)

Introduzione al MATLAB, nozioni preliminari, potenzialità e limiti del software, programmare con l’editor di MATLAB; introduzione all’uso dei Toolboxes: Genetic Algorithm, Neural Networks, Fuzzy Logic, Signal Processing, Wavelet, Algoritmi PCA e ICA, EEGLAB, ICA-lab, FAST-ICA.


Introduction to the Environmental Signals (CFU 1)

Concept of environmental signal; important technical signals and environmental data; database manipulation of an environmental nature, elements of data mining, information management, and environmental data.

Recording techniques of environmental signals (CFU 1)

Acquisition systems and A / D conversion, acquisition interfaces, sensors for recording environmental signals; collection and selection of samples, statistical systems for the treatment of environmental data; treatment outliers; statistical decision theory.

Advanced Signal Processing of Environmental Data and Signals (CFU 1)

Implementation of algorithms for the analysis of multi-resolution and multi-dimensional environmental signals; models for the simulation of environmental systems, numerical processing of environmental signals, noise, design and implementation of circuits and systems for the treatment of environmental signals examples of meteorological data and satellite; laboratory exercises.
Books Uncini A., “ Elaborazione Adattiva dei Segnali”, Aracne Editore.

Principe, N. R. Euliano, W. C. Lefebvre, “Neural and Adaptive Systems: Fundamental through Simulations”, J. Wiley & Sons.

Bishop C.M., “Pattern Recognition and Machine Learning”, Oxford University Press.

Hyvarinen A., J. Karhunen, E. Oja, “Independent Component Analysis”, J. Wiley & Sons.
Traditional teaching method Yes
Distance teaching method No
Mandatory attendance No
Written examination evaluation No
Oral examination evaluation Yes
Aptitude test evaluation No
Project evaluation Yes
Internship evaluation No
Evaluation in itinere No
Practice Test No

Further information

No document in this course
No news posted
No class timetable posted

Module: ENVIRONMENTAL DATA PROCESSING

Degree course Environmental Enginnering
Curriculum NUOVE TECNOLOGIE PER LA TUTELA DEL TERRITORIO E DELL’AMBIENTE
Learnings PS.LM35.IND012.2013-2014
Academic Year 2016/2017
ECTS 6
Scientific Disciplinary Sector ING-IND/31
Year First year
Time unit Second semester
Class hours 48
Educational activity Related and integrative training activities

Single group

Professor MARIO VERSACI
Objectives The course has the objective of initiating students to the analysis and synthesis of mono and two-dimensional signals with the help of statistical techniques and analytical- numerical implemented at the computer.
Programme Elements of the computer programming, MatLab instructions - Octave, analog, digital signals, Fourier series, Fourier transform, convergence. Implementation aspects. statistical analysis of a database. Techniques of feature extraction. of environmental database structure. implementation aspects. Notes on the quality 'of a database and its assessment.
Books E. Giusti, Analisi Matematica – Bollati Boringhieri
M. Luise, M. Vitetta, Teoria dei Segnali – Mcgraw Hill
Traditional teaching method Yes
Distance teaching method No
Mandatory attendance No
Written examination evaluation No
Oral examination evaluation Yes
Aptitude test evaluation No
Project evaluation Yes
Internship evaluation No
Evaluation in itinere No
Practice Test No

Further information

No document in this course
No news posted
No class timetable posted
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