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检索条件"机构=Department of Cybernetics and Research Centre Data-Algorithms-Decision Making"
42 条 记 录,以下是1-10 订阅
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Adaptive choice of scaling parameter in derivative-free local filters
Adaptive choice of scaling parameter in derivative-free loca...
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作者: Duník, Jindřich Šimandl, Miroslav Straka, Ondřej Department of Cybernetics Research Centre Data-Algorithms-Decision Making University of West Bohemia Czech Republic
The paper deals with adaptive choice of the scaling parameter in derivative-free local filters. In the last decade several novel local derivative-free filtering methods have been proposed. These methods exploiting Sti... 详细信息
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Gaussian mixtures proposal density in particle filter for track-before-detect
Gaussian mixtures proposal density in particle filter for tr...
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2009 12th International Conference on Information Fusion, FUSION 2009
作者: Straka, Ondrej Šimandl, Miroslav Duník, Jindrich Department of Cybernetics Research Centre Data-Algorithms-Decision Making University of West Bohemia Czech Republic
The paper deals with state estimation for the track-before-detect approach using the particle filter. The focus is aimed at the track initiation proposal density of the particle filter which considerably affects estim... 详细信息
来源: 评论
Truncated unscented particle filter
Truncated unscented particle filter
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作者: Straka, Ondřej Duník, Jindřich Šimandl, Miroslav Research Centre Data-Algorithms-Decision Making Department of Cybernetics University of West Bohemia Pilsen Czech Republic
The problem of state estimation of nonlinear stochastic dynamic systems with nonlinear inequality constraints is treated. The paper focuses on a particle filtering approach, which provides an estimate of the state in ... 详细信息
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A software framework and tool for nonlinear state estimation
A software framework and tool for nonlinear state estimation
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15th IFAC Symposium on System Identification, SYSID 2009
作者: Straka, Ondšej Flídr, Miroslav Duník, Jindšich Šimandl, Miroslav Department of Cybernetics and Research Centre Data - Algorithms - Decision Making University of West Bohemia Univerzitní 8 30614 Plzeň Czech Republic
The goal of the article is to describe a software framework designed for nonlinear state estimation of discrete time dynamic systems. The framework was designed with the aim to facilitate implementation, testing and u... 详细信息
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Framework for implementing and testing nonlinear filters
Framework for implementing and testing nonlinear filters
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作者: Flídr, Miroslav Duník, Jindřich Straka, Ondřej Švácha, Jaroslav Šimandl, Miroslav Department of Cybernetics and Research Centre Data - Algorithms - Decision Making University of West Bohemia In Pilsen Univerzitní 8 30614 Plzeň Czech Republic
The aim of this paper is to present a software framework facilitating implementation, testing and use of various nonlinear estimation methods. This framework is designed to offer an easy to use tool for state estimati... 详细信息
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Nonlinear filtering toolbox for continuous stochastic systems with discrete measurements
Nonlinear filtering toolbox for continuous stochastic system...
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作者: Švácha, Jaroslav Šimandl, Miroslav Straka, Ondřej Flídr, Miroslav Research Centre Data Algorithms and Decision Making Department of Cybernetics University of West Bohemia In Pilsen Univerzitní 8 306 14 Plzeň Czech Republic
The paper deals with a problem of state estimation for nonlinear continuous stochastic systems with discrete-time measurements. A general recursive solution of the estimation problem given by the Bayesian rule and by ... 详细信息
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Particle based probability density fusion with differential Shannon entropy criterion
Particle based probability density fusion with differential ...
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作者: Ajgl, Jiří Šimandl, Miroslav Department of Cybernetics and Research Centre Data - Algorithms - Decision Making Faculty of Applied Sciences University of West Bohemia Pilsen Czech Republic
This paper focuses on a decentralised nonlinear estimation problem in a multiple sensor network. The stress is laid on the optimal fusion of probability densities conditioned by different data. The probability density... 详细信息
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An efficient constrained Gaussian particle filter
An efficient constrained Gaussian particle filter
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作者: Straka, Ondřej Šimandl, Miroslav Department of Cybernetics and Research Centre Data-Algorithms-Decision Making Faculty of Applied Sciences University of West Bohemia Univerzitní 8 306 14 Pilsen Czech Republic
The paper deals with a state estimation of nonlinear stochastic dynamic systems subject to a nonlinear inequality constraint. A special focus is paid to particle filters, which provide an estimate of the whole probabi... 详细信息
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A survey of sample size adaptation techniques for particle filters
A survey of sample size adaptation techniques for particle f...
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15th IFAC Symposium on System Identification, SYSID 2009
作者: Straka, Ondšej Šimandl, Miroslav Department of Cybernetics and Research Centre: Data - Algorithms - Decision Making Faculty of Applied Sciences University of West Bohemia Univerzitní 8 306 14 Plzeň Czech Republic
The paper deals with the particle filter in discrete-time nonlinear non-Gaussian system state estimation. One of the key parameters affecting estimate quality of the particle filter is the sample size. In the literatu... 详细信息
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The development of a randomised unscented Kalman filter
The development of a randomised unscented Kalman filter
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作者: Duník, Jindřich Straka, Ondřej Šimandl, Miroslav Department of Cybernetics and Research Centre Data-Algorithms-Decision Making Faculty of Applied Sciences University of West Bohemia Univerzitní 8 306 14 Pilsen Czech Republic
The paper deals with state estimation of nonlinear stochastic dynamic systems. Traditional filters providing local estimates of the states, such as the extended Kalman filter, unscented Kalman filter or the cubature K... 详细信息
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