Two-Scale Stochastic Systems

Two-scale systems described by singularly perturbed SDEs have been the subject of ample literature. However, this new monograph develops subjects that were rarely addressed and could be given the collective description "Stochastic Tikhonov-Levinson theory and its applications." The book provides a mathematical apparatus designed to analyze the dynamic behaviour of a randomly perturbed system with fast and slow variables. In contrast to the deterministic Tikhonov-Levinson theory, the basic model is described in a more realistic way by stochastic differential equations. This leads to a number of new theoretical questions but simultaneously allows us to treat in a unified way a surprisingly wide spectrum of applications like fast modulations, approximate filtering, and stochastic approximation.Two-scale systems described by singularly perturbed SDEs have been the subject of ample literature. However, this new monograph develops subjects that were rarely addressed and could be given the collective description "Stochastic Tikhonov-Levinson theory and its applications." The book provides a mathematical apparatus designed to analyze the dynamic behaviour of a randomly perturbed system with fast and slow variables. In contrast to the deterministic Tikhonov-Levinson theory, the basic model is described in a more realistic way by stochastic differential equations. This leads to a number of new theoretical questions but simultaneously allows us to treat in a unified way a surprisingly wide spectrum of applications like fast modulations, approximate filtering, and stochastic approximation.

The authors are the creators of this theory No competing book Interesting potential applications and further research Includes supplementary material: sn.pub/extras

Inhalt
0 Warm-up.- 1 Toolbox: Moment Bounds for Solutions of Stable SDEs.- 2 The Tikhonov Theory for SDEs.- 3 Large Deviations.- 4 Uniform Expansions for Two-Scale Systems.- 5 Two-Scale Optimal Control Problems.- 6 Applications.- A.1 Basic Facts About SDEs.- A.1.1 Existence and Uniqueness of Strong Solutions for SDEs with Random Coefficients.- A.1.2 Existence and Uniqueness with a Lyapunov Function.- A.1.3 Moment Bounds for Linear SDEs.- A.1.4 The Novikov Condition.- A.2 Exponential Bounds for Fundamental Matrices.- A.2.1 Uniform Bound in the Time-Homogeneous Case.- A.2.2 Nonhomogeneous Case.- A.2.3 Models with Singular Perturbations.- A.3 Total Variation Distance and Hellinger Processes.- A.3.1 Total Variation Distance and Hellinger Integrals.- A.3.2 The Hellinger Processes.- A.3.3 Example: Diffusion-Type Processes.- A.4 Hausdorff Metric.- A.5 Measurable Selection.- A.5.1 Aumann Theorem.- A.5.2 Filippov Implicit Function Lemma.- A.5.3 Measurable Version of the Carathéodory Theorem.- A.6.1 Notations and Preliminaries.- A.6.2 Integration of Stochastic Kernels.- A.6.3 Distributions of Integrals.- A.6.4 Compactness of the Limit of Attainability Sets.- A.6.5 Supports of Conditional Distributions.- A.7 The Komlós Theorem.- Historical Notes.- References.