1.152 Random Processes in Engineering
Full-distribution and second-moment description of random processes and fields. Strict and broad stationarity and ergodicity. Gaussian random functions: physical-space and frequency-domain characterization, integration, differentiation, filtering and simulation. Poisson and related processes. Markov processes in discrete and continuous time. Poisson and Markov models with rewards. Level crossing and extremes of Gaussian, Poisson and Markov processes. Scale-invariant processes: self-similarity and multifractality. Emphasizes engineering applications. Students must write a term paper on a relevant topic of their choice.
This class has 1.151 as a prerequisite.
1.152 will not be offered this semester. It will be instructed by D. Veneziano.
Lecture occurs 11:00 AM to 12:30 PM on Tuesdays and Thursdays in 1-242.
This class counts for a total of 12 credits.
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