The course is a one semester advanced class in signal processing with specific application to biomedical signals.
Introduction & review - Properties of biological signals - Statistical characterization of signals - Stochastic processes - Linear Time-invariant(LTI) systems, frequencyresponseand transfer function. - Finite and infinite impulseresponsefilters(FIR & IIR). Linear-phaseFIR filterdesign by windowsmethod. IIR filterdesign by polesand zerosplacement. ClassicalIIR filters. - Autoregressive(stochastic) processesasmodelsof signals. AR modelsorderselection. - Estimationtheorybasics: accuracy, trueness, precision.
Spectral analysis - Non parametric and Parametric spectral estimators - Spectral analysis of non-evenly sampled series
Source separation - Enhancement of repetitive patterns through averaging - Mean and exponential average - Cross-correlation& matchedfilters
Long time correlations and fractals signals - Long memory processes - Estimation of scaling in time series
Entropies and regularity - Entropy as a measure of information rate - Entropy as a measure of regularity - Entropy practical estimators
Prerequisiti e modalità di esame
The grading of the class is performed through a written examination (plus a quick oral interview where the results of the written examination are discussed) which can be substituted with a project assigned under request by the instructor.