Observation Noise-Gain Detection for Markov Chains Observed through scaled Brownian Motion
Date
2008
Authors
Bensoussan, Alain
Malcolm, William
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
In this preliminary article we consider the problem of estimating an unknown noise-gain for a Markov chain observed through a scaled Brownian motion. It is assumed that the unknown noise-gain is time invariant. Two objectives are addressed in this work, 1) compute an estimation scheme that is fast, and 2) compute an estimation scheme without recourse to stochastic integration. To address the first objective we avoid the Expectation Maximization (EM) algorithm, instead we develop an estimation scheme for a finite number of candidate model hypotheses. To address the second objective we develop a version of the Gauge-Transformation technique introduced by J. M. C. Clark.
Description
Keywords
Keywords: Detection; Filtering; Martingales; Reference probability; Wonham filter; Brownian movement; Markov processes; Estimation Detection; Filtering; Martingales; Reference probability; Wonham filter
Citation
Collections
Source
Proceedings of IEEE Conference on Decision and Control 2008
Type
Conference paper