Approximating a diffusion by a finite-state hidden Markov model

DOI10.1016/j.spa.2016.11.004zbMath1373.60132arXiv0906.0259OpenAlexW2560266776MaRDI QIDQ2360239

Sean P. Meyn, Ioannis Kontoyiannis

Publication date: 30 June 2017

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0906.0259

zbMATH Keywords

stochastic Lyapunov functionhidden Markov modelMarkov processdiscrete spectrumhypoelliptic diffusion

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Diffusion processes (60J60) Continuous-time Markov processes on discrete state spaces (60J27) Transition functions, generators and resolvents (60J35)

Related Items (2)

Geometric ergodicity in a weighted Sobolev space ⋮ Approximations for the distribution of perpetuities with small discount rates

Cites Work

• Markov chains and stochastic stability
• Exit probabilities and optimal stochastic control
• Fluctuations of the entropy production in anharmonic chains
• Essential spectral radius for Markov semigroups. I: Discrete time case
• Martingale problems for large deviations of Markov processes
• Large deviations asymptotics and the spectral theory of multiplicatively regular Markov proces\-ses
• Spectral theory and limit theorems for geometrically ergodic Markov processes
• Multiplicative ergodicity and large deviations for an irreducible Markov chain.
• Large and moderate deviations and exponential convergence for stochastic damping Hamiltonian systems.
• Exponential and uniform ergodicity of Markov processes
• Transportation-information inequalities for Markov processes
• Spectral gap of positive operators and applications
• Two-sided bounds for degenerate processes with densities supported in subsets of \(\mathbb R^N\)
• Comparing Markov Chains: Aggregation and Precedence Relations Applied to Sets of States, with Applications to Assemble-to-Order Systems
• Stability of Markovian processes II: continuous-time processes and sampled chains
• Stability of Markovian processes III: Foster–Lyapunov criteria for continuous-time processes
• General Irreducible Markov Chains and Non-Negative Operators
• Asymptotic evaluation of certain markov process expectations for large time. IV
• Inequalities in Theorems of Ergodicity and Stability for Markov Chains with Common Phase Space. I
• Asymptotic evaluation of certain markov process expectations for large time, II
• Asymptotic evaluation of certain Markov process expectations for large time—III
• Optimal Kullback-Leibler Aggregation via Spectral Theory of Markov Chains
• Discrete Dynamic Programming with Sensitive Discount Optimality Criteria
• Unsupervised learning by probabilistic latent semantic analysis
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Approximating a diffusion by a finite-state hidden Markov model