ECE 209Statistical Learning for Biosignal Processing
Medical device systems increasingly measure biosignals from multiple sensors, requiring computational analyses of complex multivariate time-varying data. The combination of statistics and algorithms produces statistical learning methods that automate the analysis of complex data. Applications within the domain of neural engineering that utilize unsupervised and supervised generative statistical modeling techniques are explored. This course assumes familiarity with key statistical methods.
Prerequisites
From the catalog: “ECE 271A-B; graduate standing.”