Pennsylvania State University 3 credits EE
This course covers basic concepts in probability, including random variables, conditioning, independence, laws of large numbers, and statistical confidence. While covering these basic probability concepts, illustrative examples drawn from Electrical and Computer Engineering topics such as communications, signal processing, networking, image processing, and control systems will be used to show engineering applications of the probability and statistical theory. The course concludes with a module on linear filtering of wide-sense stationary processes, including in the frequency domain via power spectral density. The course consists of lectures and recitations. Recitations reinforce concepts learned in lecture through problem solving. Recitations are also used to study applications such as information theory and signal detection using binary hypothesis testing. Laboratory exercises demonstrate the use of software packages for simulation and calculations.
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