Results 161 to 170 of about 7,374 (201)
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An Improvement to Unscented Transformation
2004This paper proposes a new sigma point selection strategy to better capture the information of a probability distribution By doing so, the non-local sampling problem inherent in the original unscented transformation (UT) is fundamentally eliminated It is argued that the improved UT (IUT) outperforms the original UT at the cost of increased but ...
Yuanxin Wu +3 more
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Multisensor constrained estimation with unscented transformation
2010 13th International Conference on Information Fusion, 2010The paper focuses on multisensor constrained estimation. The possibility of an extension of a current unconstrained fusion technique is discussed for equality constrained estimates. Basic approaches to multisensor constrained estimation with fusion centre are proposed and discussed. The stress is laid on the constraint in or outside the estimation loop
Jirí Ajgl, Miroslav Simandl
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Automatic Uncertainty Propagation Based on the Unscented Transform
2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2020Automatic uncertainty propagation reduces the effort for computation of uncertainty and is thus a useful tool in a variety of applications. Typically, such tools utilize Taylor series approximations (in particular linearization) or Monte Carlo Methods to perform the calculations.
Dailys Arronde Pérez +2 more
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Simplifying Mixture Models Using the Unscented Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demanding due to the large number of components involved in the model. We propose a novel algorithm for learning a simplified representation of a Gaussian mixture, that is based on ...
Jacob Goldberger +2 more
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A novel simplex unscented transform and filter
2007 International Symposium on Communications and Information Technologies, 2007In this paper, we propose a new simplex unscented transform, and a new filter - modify unscented Kalman filter (MUKF) based on this transform. It has less compute consumption than UKF, SUKF (Julier and Uhlmann, 2004) and EKF (Athans et al., 1968). Computer simulation show that this filter has the same performance as UKF and SUKF; and we analysis the ...
Wei Ping, Xiao Xian-Ci
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On the convergence rate of the unscented transformation
Annals of the Institute of Statistical Mathematics, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ahn, Kwang Woo, Chan, Kung-Sik
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The spherical simplex unscented transformation
Proceedings of the 2003 American Control Conference, 2003., 2004This paper describes a new and better-behaved sigma point selection strategy for the unscented transformation (UT). The UT approximates the result of applying a specified nonlinear transformation to a given mean and covariance estimate. The UT works by constructing a set of points, referred to as sigma points, which have the same known statistics as ...
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Scaling parameter in unscented transform: Analysis and specification
2012 American Control Conference (ACC), 2012The paper deals with an analysis of the scaling factor of the unscented transform as a method to provide approximate means and covariance matrices of random variables in nonlinear systems. It is a basis of the unscented Kalman filter, which provides a state estimate of nonlinear stochastic dynamic systems.
Ondrej Straka +2 more
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Unscented Transformations for Probabilistic Load Flow
2018 North American Power Symposium (NAPS), 2018Distributed energy resources (DER) systems introduce uncertainties in the electrical grid that cannot be addressed by classical deterministic methods. Power system analytic tools, such as Load Flow (LF), should be revisited to address such uncertainties and dependencies.
Juan D. Franco Canon, Saeed Jafarzadeh
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A more robust unscented transform
SPIE Proceedings, 2001The unscented transformation is extended to use extra test points beyond the minimum necessary to determine the second moments of a multivariate normal distribution. The additional test points can improve the estimated mean and variance of the transformed distribution when the transforming function of its derivatives have discontinuities.
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