[图书][B] Stochastic equations in infinite dimensions
G Da Prato, J Zabczyk - 2014 - books.google.com
Now in its second edition, this book gives a systematic and self-contained presentation of
basic results on stochastic evolution equations in infinite dimensional, typically Hilbert and …
basic results on stochastic evolution equations in infinite dimensional, typically Hilbert and …
[图书][B] Ergodic behavior of Markov processes: with applications to limit theorems
A Kulik - 2017 - books.google.com
The general topic of this book is the ergodic behavior of Markov processes. A detailed
introduction to methods for proving ergodicity and upper bounds for ergodic rates is …
introduction to methods for proving ergodicity and upper bounds for ergodic rates is …
Well-posedness and regularity for quasilinear degenerate parabolic-hyperbolic SPDE
B Gess, M Hofmanová - The Annals of Probability, 2018 - JSTOR
We study quasilinear degenerate parabolic-hyperbolic stochastic partial differential
equations with general multiplicative noise within the framework of kinetic solutions. Our …
equations with general multiplicative noise within the framework of kinetic solutions. Our …
[HTML][HTML] Central limit theorem for Markov processes with spectral gap in the Wasserstein metric
T Komorowski, A Walczuk - Stochastic Processes and their Applications, 2012 - Elsevier
Suppose that {Xt, t≥ 0} is a non-stationary Markov process, taking values in a Polish metric
space E. We prove the law of large numbers and central limit theorem for an additive …
space E. We prove the law of large numbers and central limit theorem for an additive …
On unique ergodicity in nonlinear stochastic partial differential equations
We illustrate how the notion of asymptotic coupling provides a flexible and intuitive
framework for proving the uniqueness of invariant measures for a variety of stochastic partial …
framework for proving the uniqueness of invariant measures for a variety of stochastic partial …
A new belief Markov chain model and its application in inventory prediction
Z He, W Jiang - International Journal of Production Research, 2018 - Taylor & Francis
The Markov chain model is widely applied in many fields, especially the field of prediction.
The discrete-time Markov chain (DTMC) is a common method for prediction. However, the …
The discrete-time Markov chain (DTMC) is a common method for prediction. However, the …
[PDF][PDF] 一种信度马尔科夫模型及应用
邓鑫洋, 邓勇, 章雅娟, 刘琪 - 自动化学报, 2012 - aas.net.cn
摘要马尔科夫链以其无后效性广泛应用于自然科学和工程技术领域. 经典的马尔科夫链并不能
反映对象状态的不确定性, 并且当状态划分边界过于清晰时, 状态转移情况不稳定 …
反映对象状态的不确定性, 并且当状态划分边界过于清晰时, 状态转移情况不稳定 …
Generalized couplings and convergence of transition probabilities
A Kulik, M Scheutzow - Probability Theory and Related Fields, 2018 - Springer
We provide sufficient conditions for the uniqueness of an invariant measure of a Markov
process as well as for the weak convergence of transition probabilities to the invariant …
process as well as for the weak convergence of transition probabilities to the invariant …
[HTML][HTML] Refined basic couplings and Wasserstein-type distances for SDEs with Lévy noises
D Luo, J Wang - Stochastic Processes and their Applications, 2019 - Elsevier
We establish the exponential convergence with respect to the L 1-Wasserstein distance and
the total variation for the semigroup corresponding to the stochastic differential equation d X …
the total variation for the semigroup corresponding to the stochastic differential equation d X …
[图书][B] Asymptotic analysis for functional stochastic differential equations
The ergodicity of SDEs and SPDEs, in which the state spaces are independent of the past,
has been studied extensively. So far, there are several approaches to investigate ergodicity …
has been studied extensively. So far, there are several approaches to investigate ergodicity …