Johns Hopkins University 3 credits Electrical and Computer Engineering
Both hypothesis testing and estimation theory are covered. The course starts with a review of probability distributions, multivariate Gaussians, and the central limit theorem. Hypothesis testing areas include simple and composite hypotheses and binary and multiple hypotheses. In estimation theory, maximum likelihood estimates and Bayes estimates are discussed. Practical problems in radar and communications are used as examples throughout the course. Prerequisite(s): EN.525.614 Probability and Stochastic Processes for Engineers or equivalent.;***Cybersecurity students only: Must complete core courses first (EN.605.621 AND EN.695.601 AND EN.695.641).;***Robotics and Autonomous Systems students only: Must complete core courses first (EN.685.621 AND EN.535.641 AND EN.535.630 AND EN.605.613).
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