The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
R.j. Elliott - One of the best experts on this subject based on the ideXlab platform.
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Optimal linear estimation and data fusion
IEEE Transactions on Automatic Control, 2006Co-Authors: R.j. Elliott, J. Van Der HoekAbstract:Optimal mean square linear estimators are determined for general uncorrelated noise. We allow the noise variance matrix in the Observation Process to be singular. This requires properties of generalized inverses which are developed in Section II. The proofs appear to be new. When there are two Observation sequences the optimal method of recursively fusing the two is determined. We derive a new formula for the covariance of the two estimates which then provides exact dynamics for a fused estimate.
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Robust detection filters for jump Markov systems with doubly stochastic Poisson Process models
Final Program and Abstracts on Information Decision and Control, 2002Co-Authors: W.p. Malcolm, R.j. ElliottAbstract:In this article we consider a dynamic M-ary detection problem when Markov chains are observed through a doubly stochastic Poisson Process. These systems are fully specified by a candidate set of parameters, whose elements are, a rate matrix for the Markov chain and a vector of Poisson intensities for the Observation model. Further, we suppose these parameter sets can switch according to the state of an unobserved Markov chain and thereby produce an Observation Process generated by time varying (jump stochastic) parameter sets. Given such an Observation Process and an assumed collection of models, we compute a filter whose solution is the estimated probabilities of each model parameter set explaining the Observation. By defining a new augmented state Process, then applying the method of reference probability, we compute matrix-valued dynamics whose solutions estimate joint probabilities for all combinations of candidate model parameter sets, and values taken by the indirectly observed state Process. These matrix-valued dynamics satisfy a stochastic integral equation with a Lebesgue-Stieltjes integrator. Using the gauge transformation techniques, we compute robust matrix-valued dynamics for the joint probabilities on the augmented state space. In these new dynamics the observed Poisson Process appears as a parameter in the fundamental matrix of a linear ordinary differential equation, rather than an integrator in a stochastic integral equation.
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M-ary detection filters for Cox Process models
ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359), 1999Co-Authors: W.p. Malcolm, R.j. ElliottAbstract:M-ary detection filters for Cox Process models are derived. The models considered consist of Poisson Observations and a discrete state Markov Process whose value determines the intensity. The detection filters presented are stochastic partial differential equations driven by an Observation Process. The probabilities which solve these equations, indicate the relative likelihood that a given dynamical system explains an Observation. A simulation study is included.
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Filtering with discrete state Observations
Proceedings of the 36th IEEE Conference on Decision and Control, 1997Co-Authors: F. Dufour, R.j. ElliottAbstract:The problem of estimating a finite state Markov chain observed via a Process on the same state space is discussed. Optimal solutions are given for both the 'weak' and 'strong' formulations of the problem. The 'weak' formulation proceeds using a reference probability and a measure change for Markov chains. The 'strong' formulation considers an Observation Process related to perturbations of the counting Processes associated with the Markov chain. In this case the 'small noise' convergence is investigated.
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New finite-dimensional filters and smoothers for noisily observed Markov chains
IEEE Transactions on Information Theory, 1993Co-Authors: R.j. ElliottAbstract:New finite-dimensional filters and smoothers that are related to the Wonham filter of a noisily observed Markov chain are obtained. In particular, finite-dimensional, recursive filters and smoothers are given for the number of jumps from state i to state j, for the occupation time of state i, and for a stochastic integral related to the drift in the Observations. These filters allow easy application of the EM algorithm for the estimation of the parameters of the Markov chain and Observation Process.
T.e. Dabbous - One of the best experts on this subject based on the ideXlab platform.
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Optimal control for a class of partially observed bilinear stochastic systems
29th IEEE Conference on Decision and Control, 1990Co-Authors: T.e. DabbousAbstract:An alternative formulation is presented for a class of partially observed bilinear stochastic control problems which is described by three sets of stochastic differential equations: one for the system to be controlled, one for the observer, and one for the control Process which is driven by the Observation Process. With this formulation, the stochastic control problem is converted to an equivalent deterministic identification problem of control gain matrices. Using standard variation arguments, the necessary conditions of optimality on the basis of which the optimal control parameters can be determined are obtained.
T. Weissman - One of the best experts on this subject based on the ideXlab platform.
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On the optimality of symbol by symbol filtering and denoising
International Symposium onInformation Theory 2004. ISIT 2004. Proceedings., 2004Co-Authors: E. Ordentlich, T. WeissmanAbstract:This paper describes the optimality of symbol by symbol filtering and denoising and considers the problem of optimally recovering a discrete-time valued stochastic Process from a noisy Observation Process. For binary Markov input Process singlet filtering and denoising are optimal. Finally, for the case of memoryless channel, large deviations performance of singlet filtering is obtained.
E. Bouza - One of the best experts on this subject based on the ideXlab platform.
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Performing Gram stain directly on catheter tips: assessment of the quality of the Observation Process
European Journal of Clinical Microbiology & Infectious Diseases, 2015Co-Authors: M. Guembe, M. J. Pérez-granda, M. L. Rivera, P. Martín-rabadán, E. BouzaAbstract:A previous study performed in our institution showed that catheter tip (CT) staining by combining acridine orange and Gram stain (GS) before culture anticipated catheter colonization with exhaustive and careful Observation by a highly trained technician. Our objective was to assess the validity values of GS without acridine orange on an external smear of CT for predicting catheter colonization and catheter-related bloodstream infection (C-RBSI). We compared different periods of Observation and the results of two technicians with different levels of professional experience. Over a 5-month period, the roll-plate technique was preceded by direct GS of all CTs sent to the microbiology laboratory. The reading was taken at ×100 by two observers with different skill levels. Each observer performed a routine examination (3 min along three longitudinal lines) and an exhaustive examination (5 min along five longitudinal lines). The presence of at least one cell was considered positive. All slides were read before culture results were known. We included a total of 271 CTs from 209 patients. The prevalence of catheter colonization and C-RBSI was 16.2 % and 5.1 %, respectively. Routine and exhaustive examinations revealed only 29.5 % and 40.9 % of colonized catheters, respectively ( p
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Performing Gram stain directly on catheter tips: assessment of the quality of the Observation Process
European Journal of Clinical Microbiology & Infectious Diseases, 2015Co-Authors: M. Guembe, M. J. Pérez-granda, P. Martín-rabadán, Marisa Rivera, E. BouzaAbstract:A previous study performed in our institution showed that catheter tip (CT) staining by combining acridine orange and Gram stain (GS) before culture anticipated catheter colonization with exhaustive and careful Observation by a highly trained technician. Our objective was to assess the validity values of GS without acridine orange on an external smear of CT for predicting catheter colonization and catheter-related bloodstream infection (C-RBSI). We compared different periods of Observation and the results of two technicians with different levels of professional experience. Over a 5-month period, the roll-plate technique was preceded by direct GS of all CTs sent to the microbiology laboratory. The reading was taken at ×100 by two observers with different skill levels. Each observer performed a routine examination (3 min along three longitudinal lines) and an exhaustive examination (5 min along five longitudinal lines). The presence of at least one cell was considered positive. All slides were read before culture results were known. We included a total of 271 CTs from 209 patients. The prevalence of catheter colonization and C-RBSI was 16.2 % and 5.1 %, respectively. Routine and exhaustive examinations revealed only 29.5 % and 40.9 % of colonized catheters, respectively (p < 0.001). In contrast, they revealed high negative predictive values for C-RBSI (96.5 % and 96.3 %, respectively). Our study shows that the yield of GS performed directly on CTs is greater when staining is performed exhaustively. However, the decision to implement this approach in daily routine will depend on the prevalence rate of catheter colonization at each institution.
Masaaki Miyakoshi - One of the best experts on this subject based on the ideXlab platform.
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Image restoration in singular Observation Processes based on complementary space component estimation
Electronics and Communications in Japan Part Ii-electronics, 2020Co-Authors: Akira Tanaka, Hideyuki Imai, Masaaki MiyakoshiAbstract:Image restoration is a problem in which an unknown original image is to be estimated from a degraded image obtained from some Observation Process. Various restoration methods have been proposed. Most of the conventional methods assume that the Observation Process is regular or almost regular. However, in general there is no guarantee that the Observation Process is regular, and the restoration performance of past methods is insufficient for a singular Observation Process. The degradation of restoration performance in a singular Observation Process arises from the fact that it is difficult to estimate the components related to the null space, which is eliminated in the Observation Process. There have recently been many studies of the properties and representations of the image signal. In one such study it was reported that the difference signal of the image approximately follows the Laplace distribution. This paper is based on that stochastic property of the image, and proposes a method of restoring images with high precision by positively estimating the image component which is eliminated in a singular Observation Process. The effectiveness of the proposed method is investigated by numerical experiment. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 88(8): 54–65, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ ecjb.20201
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Image restoration with kernel component estimation in singular Observation Process
IEEE Workshop on Statistical Signal Processing 2003, 2003Co-Authors: Akira Tanaka, Hideyuki Imai, Masaaki MiyakoshiAbstract:A new approach to restore images degraded by singular Observation Processes is proposed. Existing image restoration filters usually assume non-singularity of Observation Processes. Therefore, we can not obtain desirable result by these filters, especially in case that the degradation Processes have high singularity. By the way, it is well known that differential images can be assumed to be Laplacian distributed random vectors. In this paper, we propose a new restoration method for singular Observation Processes based on this statistical knowledge about images. A numerical example is also presented to verify the efficacy of the proposed method.
