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The Sequential Probability Ratio Test (SPRT) is a classical detector for problems with an unfixed sample size. Though it is optimal under some conditions, SPRT can be directly used only for a binary hypothesis with exactly known distributions. In this paper, sequential detection problem with an uncertain hypothesis distribution is considered, in which the uncertain distribution is formulated in a...
Detection with multiple distributions is considered. Rather than formulating the problem with multiple hypotheses, we formulate the problem in a binary hypothesis testing framework by a multiple model approach. Three classes of the Multi-Model Detection (MMD) problems are considered: simplex, compound, and mixture. Three concepts of optimality are given for these three problems, including Uniformly...
A fault detection, identification, estimation and state estimation (FDIESE) problem involves joint decision and estimation (JDE). Decision contains detection and identification, while estimation is for fault severeness and system state. Both detection and identification are highly coupled with estimation and a fault is identified after detection. To solve this problem, an approach named nested joint...
This paper presents a new approach based on extension deformation for extended object tracking (EOT). In this approach, the extension of an object is assumed to be deformed from a reference extension by moving some control points in the latter to those in the former. That is, the properties of an extension can be fully captured by the control points, given the reference extension. Thus, modeling and...
Estimation for discrete-time stochastic systems with parameters varying in a continuous space is considered in this paper. Justified by an analysis of model approximation, a novel approach, called hybrid grid multiple model (HGMM), is proposed for state estimation. The model set used by HGMM is a combination of a fixed coarse grid and an adaptive fine grid to cover the mode space with a relatively...
This paper presents a multiple-model hypothesis testing (MMHT) approach using a representative model (RM) for detecting unknown events that may have multiple distributions. It addresses various difficulties of MMHT for composite, multivariate, nondisjoint, and mis-specified hypothesis sets with correlated observations, and decides which region of the mode space covered by the model set is better....
A polytopic model (PM) structure is often used in the areas of automatic control and fault detection as an alternative multiple model approach that explicitly allows for interpolation among local models. The model that is valid, usually unknown, is represented by a weighed combination of models in a given model set. Proposed is a novel approach to PM estimation by modeling the set of PM weights as...
A variable-structure multiple-model (VSMM) approach, named equivalent-model augmentation (EqMA), is proposed. Here the model set is augmented by a variable model intended to best match the unknown true mode. To fully utilize the information provided by model sequences, this variable model depends on the true mode at the previous time. Thus different previous models correspond to different augmenting...
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