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Neural network training with optimal bounded ellipsoid algorithm
Neural Computing and Applications, 2008Compared to normal learning algorithms, for example backpropagation, the optimal bounded ellipsoid (OBE) algorithm has some better properties, such as faster convergence, since it has a similar structure as Kalman filter. OBE has some advantages over Kalman filter training, the noise is not required to be Guassian.
José de Jesús Rubio +2 more
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Rejection of Bounded Disturbances via Invariant Ellipsoids Technique
Proceedings of the 45th IEEE Conference on Decision and Control, 2006In this paper an approach based on invariant ellipsoids is applied to the problem of persistent disturbance rejection by means of static state-feedback control. Dynamic system is supposed to be linear time-invariant and affected by unknown-but-bounded exogenous disturbances.
Boris T. Polyak +3 more
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$Q$ Bounds for Planar and Ellipsoidal Antennas
IEEE Transactions on Antennas and Propagation, 2017The procedure for numerically deriving equivalent circuits for the six lowest-order modes of arbitrarily shaped, electrically small antennas is reviewed. Element values and the effective radius are tabulated for thin prisms, spheroids, and ellipsoids with a wide range of aspect ratios.
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Recent developments in optimal bounding ellipsoidal parameter estimation
Mathematics and Computers in Simulation, 1990Abstract The Optimal Bounding Ellipsoid (OBE) algorithms are viable alternatives to conventional adaptive filtering algorithms in situations where the noise does not satisfy the usual stationarity and whiteness assumptions. An example is shown in which the performance of an OBE algorithm is seen to be markedly superior to that of the recursive least ...
Ashok K. Rao, Yih-Fang Huang
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Limit behavior of ellipsoids bounding attainable sets
Journal of Optimization Theory and Applications, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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An ellipsoid bounding of reachable systems with delay and bounded peak inputs
IFAC Proceedings Volumes, 2003Abstract Linear systems with constant coefficients and time-varying delays are considered. We address the problem of finding an ellipsoid that bounds the set of the states (in the Euclidean space) that are reachable from the origin in finite time by inputs with peak value that is bounded by a prechosen positive scalar.
Fridman Emilia, Shaked Uri
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Updating of Bounding Ellipsoids Cut Simultaneously by Two Non-Parallel Linear Bounds
IFAC Proceedings Volumes, 2000Abstract An algorithm is presented to compute the minimum-volume ellipsoid, from a parametric family, containing the intersection of an ellipsoid and the region between two non-parallel hyperplanes. The ellipsoid is optimised by solving a cubic equation, rather than the quadratic in the case where the hyperplanes are parallel; the rest of the ...
P.F. Weston, J.P. Norton
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Neural Networks Training with Optimal Bounded Ellipsoid Algorithm
2007Compared to normal learning algorithms, for example backpropagation, the optimal bounded ellipsoid (OBE) algorithm has some better properties, such as faster convergence, since it has a similar structure as Kalman filter. OBE has some advantages over Kalman filter training, the noise is not required to be Guassian.
Jose de Jesus Rubio, Wen Yu
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Unifying past and recent developments in bounded ellipsoid processing
1993 IEEE International Symposium on Circuits and Systems, 2002A general class of optimal bounding ellipsoid (OBE) algorithms, including all methods published to date, is unified into a single framework called the unified OBE (UOBE) algorithm. Different instances of UOBE are distinguished by their weighting policies and the criteria for determining optimal weight values.
J.R. Deller, M. Nayeri
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