BME6433
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Biological Statistical Signal Processing
Description
This course will cover advanced topics in statistical signal processing of biological signals. The first section of the course will cover general linear models their applications to analysis of experimental data that are both univariate and multivariate. The second part of the course will cover bayesian estimation, monte-carlo simulations, time-series analysis, discrete and continuous stochastic processes, spectral estimation and time-frequency analysis. Course work will involve hands-on projects based on analysis of real biomedical signals. Pre-requisites: Digital Signal Processing, Biological Signal and Systems.
Minimum Credits
3
Maximum Credits
3
Repeat for Credit
No
Required Requisite(s):
007648
Semesters Typically Offered
Spring