What are some applications of the Kalman filter?

This paper develops a subordinated stochastic process model for asset prices, where the directing process is identified as information. Motivated by recent. stochastic process. Mutual information based distance measure can thus be used to compare texts written by different authors or to build phylogenies of ... Probability in the Informational and Engineering Sciences ... Stochastics: An International Journal of Probability and Stochastic Processes (formerly Stochastics ... Jun 6, 2018 ... Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While ... While classical state-space reconstruction won't work on stochastic processes, such processes do have state-space representations [11], and, in the special ... The first one for obtaining concentration of Markov chains is to establish transport- entropy inequalities in the process level. This was begun again by Marton ... processes. The essence of this approach consists of: an accumulation and evaluation of Marcovian stochastics via macro functional of the stochastic process; use ... Mar 17, 2025 ... ... stochastic process governed by statistical mechanics. These ... The toroidal model acknowledges that energy and information distributions follow ... Feb 8, 2012 ... ... informational privacy is the high uncertainty about ... stochastic processes, which fit into the Binomial Option Pricing Model (BOPM). Apr 4, 2006 ... The dynamic features are governed by the information flow, modeled as a stochastic volatility process, and generalize standard ARCH ...