NIKIFOROV , Igor

This paper addresses the problem of multiple hypothesis testing (detection and isolation of mean vectors) in the case of Gaussian linear model with nuisance parameters. An invariant constrained asymptotically uniformly minimax test is proposed to solve this problem. The invariance of the test with respect to the nuisance parameters is obtained...

This paper addresses the problem of multiple hypothesis testing (detection and isolation of mean vectors) in the case of Gaussian linear model with nuisance parameters. An invariant constrained asymptotically uniformly minimax test is proposed to solve this problem. The invariance of the test with respect to the nuisance parameters is obtained...

This paper studies the problem of classifying some Gaussian samples into one of two parametric probabilistic models, also called sources, when the parameter and the a priori probability of each source are unknown. Each source is governed by an univariate normal distribution whose mean is unknown. A training sequence is available for each source...

International audience

International audience

The anomaly localization in distributed networks can be treated as a multiple hypothesis testing (MHT) problem and the Bayesian test with 0-1 loss function is a standard solution to this problem. However, For the anomaly localization application, the cost of different false localization varies, which cannot be reflected by the 0 - 1 loss...

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National audience

The railway centerline is defined by a polygonal line with some level of uncertainty in the train onboard database. The goal of this paper is to estimate the train speed by GPS and to study the impact of railway centerline uncertainty on the speed estimation. The equations for first two moments of the estimated speed are obtained and compared...

Two models of railway centerline are considered. The first, "ideal", model is composed of straight line segments, cubic parabola transition curves and arcs of circles, defined by parametric equations. The second "nonideal", model represents a piecewise linear approximation of the "ideal" model. The goal of this paper is to estimate the...

National audience

The problem of detecting an anomaly from a limited number of noisy tomographic projections is addressed from the statistical point of view. An unknown two (or three)-dimensional scene is composed of a background, considered as a nuisance parameter, with a possibly hidden anomaly. A parametric approach is proposed to reduce the lack of a priori...

International audience

International audience

International audience

A Bayesian test has been previously proposed for a multiple hypothesis testing (MHT) problem with a quadratic loss function such that this problem can fit with some real applications where the concurrent hypotheses should be distinguished. However, this MHT problem as well as this quadratic loss function are insufficient for some other...

National audience

Two models of railway centerline are considered. The first, "ideal", model is composed of straight line segments, cubic parabola transition curves and arcs of circles, defined by parametric equations. The second "nonideal", model represents a piecewise linear approximation of the "ideal" model. The goal of this paper is to estimate the...

National audience

The railway centerline is defined by a polygonal line with some level of uncertainty in the train onboard database. The goal of this paper is to estimate the train speed by GPS and to study the impact of railway centerline uncertainty on the speed estimation. The equations for first two moments of the estimated speed are obtained and compared...

The Bayesian test with 0—1 loss function is a standard solution to solve a multiple hypothesis testing problem in the Bayesian framework. For a large number of applications (like the intrusion detection, the anomaly detection,…) the alternative hypotheses have quite different importance and 0—1 loss function does not reflect the reality. The...

The Bayesian test with 0—1 loss function is a standard solution to solve a multiple hypothesis testing problem in the Bayesian framework. For a large number of applications (like the intrusion detection, the anomaly detection,…) the alternative hypotheses have quite different importance and 0—1 loss function does not reflect the reality. The...

It is assumed that the observations represent a linear superposition of unknown nuisance parameters (stochastic or deterministic), random noise and a system parameter abruptly changing its current value from nominal to abnormal at an unknown but non-random change-point. It is assumed that this statistical model characterizes the cyber-physical...

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