The problem of detecting a single anomalous process among a finite number M of
processes is considered. At each time, a subset of the processes can be observed, and the …

Detection of anomalies among a large number of processes is a fundamental task that has
been studied in multiple research areas, with diverse applications spanning from spectrum …

The drawdown process of a one-dimensional regular diffusion process X is given by X
reflected at its running maximum. The drawup process is given by X reflected at its running …

Detecting changes with multiple sensors has received significant attention in the literature. In
many practical applications such as critical infrastructure monitoring and modeling of …

In this paper, we propose a new drawdown-based regime-switching (DBRS) Lévy insurance
model in which the underlying drawdown process is used to model an insurer's level of …

The problem of detecting a single anomalous process among a finite number M of
processes is considered. We examine a composite hypothesis case, where observations of …

The automotive industry requirements for vehicle weight reduction, weight containment,
improved part functionality and passenger safety have resulted in the increased use of steel …

A quickest change detection problem is considered in a sensor network with observations
whose statistical dependency structure across the sensors before and after the change is …

We consider the problem of detecting abrupt parameter changes in a stochastic regression
with unknown noise distribution. The process changes at some unknown point of time …

We study a Wiener disorder problem of detecting the minimum of N change-points in N
observation channels coupled by correlated noises. It is assumed that the observations in …