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Wayne State University Dissertations
Averaging principle, complexity comparison, Identification system, Large deviations, non-homogeneity, Two-time-scale system
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Large Deviations Of Stochastic Systems And Applications, Qi He
Large Deviations Of Stochastic Systems And Applications, Qi He
Wayne State University Dissertations
This dissertation focuses on large deviations of stochastic systems with applications to optimal control and system identification. It encompasses analysis of two-time-scale Markov processes and system identification with regular and quantized data. First, we develops large deviations principles for systems driven by continuous-time Markov chains with twotime scales and related optimal control problems. A distinct feature of our setup is that the Markov chain under consideration is time dependent or inhomogeneous. The use of two time-scale formulation stems from the effort of reducing computational complexity in a wide variety of applications in control, optimization, and systems theory. Starting with a …