Course Detail
Course Components:
This course will cover advanced topics in statistical processing of biological signals, including topics typically covered in graduate courses on statistical analysis and stochastic processes, but centered around biomedical engineering applications. Analyses will focus on signal decomposition (e.g., in frequency spaces), extracting information from noisy signals, and modern statistics. Specific topics will include time-series analyses, discrete and continuous stochastic processes, spectral estimation and time-frequency analysis, general linear models, Bayesian estimation, and bootstrapping. Prerequisites: Calculus, Signals & Systems, and experience in Mathlab or a similar language.