On filtering of Markov chains in strong noise
P. Chigansky
Abstract
The filtering problem for finite state Markov chains is revisited, when the intensity of the observation noise increases. We give a description of conditional measure concentration around the invariant distribution of the signal and derive asymptotic expressions for the performance indices of the MMSE and MAP filtering estimates.
Create a lesson
Related papers
Boolean Small-Ball Inequalities for Discrepancy Theory
Emrullah Akbas, Suvrit Sra
Markovian renormalisation for percolation in high-dimension: Semi-decidability of mean field behavior
Arthur Blanc-Renaudie
Point process convergence of large inradii of Poisson-Laguerre tessellations
Matthias Schulte, Martina Švarc Petráková
Interpolation of Gaussian Free Fields via Random Matrices
Gabriel Raposo
Almost-Uniform Bayesian Convergence to the Truth Is Not Characterized by Countable Additivity on Conditional Hitting Times
M. Ali Khan, Arthur Paul Pedersen, Maxwell B. Stinchcombe
The skeleton-blocks decomposition of Bienaymé trees, and applications to their local convergence
Marc Bernard, Robin Stephenson