Bioengineering informatics

A.Y. 2015/2016
Lesson for
6
Max ECTS
48
Overall hours
Language
English

Course structure and Syllabus

Linea Crema
Active edition
Yes
Responsible
Lessons: 48 hours
Professor: Sassi Roberto
Syllabus
The course is a one semester advanced class in signal processing (for feature extraction) &
machine learning (for classification) with specific application to biomedical signals.

The list of topics will be:

Introduction & review
Properties of biological signals
Statistical characterization of signals
Stochastic processes

Spectral analysis
Non parametric and Parametric spectral estimators
Spectral analysis of non-evenly sampled series

Source separation
(not-blind) Enhancement of repetitive patterns through averaging
Mean, median and exponential average
Robust averaging techniques
Blind source separation

Entropies and regularity
Entropy as a measure of information rate
Entropy as a measure of regularity
Entropy practical estimators
Multiscale entropy

Long time correlations and fractals signals
Long memory processes
Estimation of scaling in time series
Multifractality

Time-frequency analysis and Wavelets
Time and frequency representation.
Linear and quadratic time frequency representation
Lesson period
Second semester
Lesson period
Second semester
Assessment methods
Esame
Assessment result
voto verbalizzato in trentesimi
Professor(s)
Reception:
By appointment (email or phone)
Dipartimento di Informatica, via Celoria 18, stanza 6004 (6 piano, ala Ovest), Milano or Polo didattico di Crema (CR)