On Some Distributed Disorder Detection
Krzysztof Szajowski

TL;DR
This paper develops a Bayesian Markov model for detecting change points in multivariate data sources with components that change homogeneity at different times, focusing on identifying influential changes in complex systems.
Contribution
It introduces a mathematical model for multivariate disorder detection with coordinate-specific change detection using Bayesian methods and simple game theory.
Findings
Effective detection of transition probability changes at specific coordinates.
Model accommodates different change times across components.
Provides a framework for reliability and intrusion detection in complex systems.
Abstract
Multivariate data sources with components of different information value seem to appear frequently in practice. Models in which the components change their homogeneity at different times are of significant importance. The fact whether any changes are influential for the whole process is determined not only by the moments of the change, but also depends on which coordinates. This is particularly important in issues such as reliability analysis of complex systems and the location of an intruder in surveillance systems. In this paper we developed a mathematical model for such sources of signals with discrete time having the Markov property given the times of change. The research also comprises a multivariate detection of the transition probabilities changes at certain sensitivity level in the multidimensional process. Additionally, the observation of the random vector is depicted. Each…
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