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Titlebook: Markov Chains and Stochastic Stability; Sean P. Meyn,Richard L. Tweedie Book 1993 Springer-Verlag London Limited 1993 Drift.Markov.Markov

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31#
發(fā)表于 2025-3-26 23:47:10 | 只看該作者
32#
發(fā)表于 2025-3-27 04:10:32 | 只看該作者
https://doi.org/10.1007/978-1-4471-3267-7Drift; Markov; Markov chain; Markov model; Symbol; Transit; calculus; communication; control; control enginee
33#
發(fā)表于 2025-3-27 08:38:49 | 只看該作者
HeuristicsThis book is about Markovian models, and particularly about the structure and stability of such models. We develop a theoretical basis by studying Markov chains in very general contexts; and we develop, as systematically as we can, the applications of this theory to applied models in systems engineering, in operations research, and in time series.
34#
發(fā)表于 2025-3-27 11:10:22 | 只看該作者
Markov ModelsThe results presented in this book have been written in the desire that practitioners will use them. We have tried therefore to illustrate the use of the theory in a systematic and accessible way, and so this book concentrates not only on the theory of general space Markov chains, but on the application of that theory in considerable detail.
35#
發(fā)表于 2025-3-27 15:34:36 | 只看該作者
Transition ProbabilitiesAs with all stochastic processes, there are two directions from which to approach the formal definition of a Markov chain.
36#
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發(fā)表于 2025-3-28 00:42:39 | 只看該作者
38#
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39#
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40#
發(fā)表于 2025-3-28 13:22:31 | 只看該作者
Invariance and TightnessIn one of our heuristic descriptions of stability, in Section 1.3, we outlined a picture of a chain settling down to a stable regime independent of its initial starting point: we will show in Part III that positive Harris chains do precisely this, and one role of π is to describe the final stochastic regime of the chain, as we have seen.
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