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Stochastic processes, stationarity, ergodicity, correlation functions, spectral densities, random inputs to linear systems; Gaussian processes. Objective: Introduce the topics of probability, random variables, and stochastic processes at the graduate level . Rigor is established by developing all results from the basic axioms (Chapters 1,2) and carefully defining and discussing such advanced notions as stochastic convergence, stochastic integrals and resolution of stochastic processes (Chapter 8). The 3rd Edition has a large number of new topics, not present in the 2nd Edition, including additional ...

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Probability, Statistics, and Stochastic Processes Peter Olofsson A Wiley-Interscience Publication JOHN WILEY & SONS, INC. New York / Chichester / Weinheim / Brisbane / Singapore / Toronto Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Fourth Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes.

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