Results 11 to 20 of about 1,928,307 (242)
On Linearly Constrained Minimum Variance Beamforming [PDF]
J. Mach. Learn. Res., 2015 Beamforming is a widely used technique for source localization in signal processing and neuroimaging. A number of vector-beamformers have been introduced to localize neuronal activity by using magnetoencephalography (MEG) data in the literature ...
Liu, Chao, Zhang, Jian
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Relaxing the Assumptions of Minimum-Variance Hedging
Journal of Agricultural and Resource Economics, 1996 The most important minimum-variance hedging ration assumptions are (a) that production is deterministic and (b) that all of the agent's wealth is invested in the cash position. Stochastic production greatly reduces optimal hedge ratios.
Sergio H. Lence
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Minimum variance constrained estimator [PDF]
Automatica, 2022 This paper is concerned with the problem of state estimation for discrete-time linear systems in the presence of additional (equality or inequality) constraints on the state (or estimate). By use of the minimum variance duality, the estimation problem is converted into an optimal control problem.
Prabhat Kumar Mishra +2 more
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State-space approach to nonlinear predictive generalized minimum variance control [PDF]
, 2010 A Nonlinear Predictive Generalized Minimum Variance (NPGMV) control algorithm is introduced for the control of nonlinear discrete-time multivariable systems.
Majecki, P.M. +3 more
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Design of generalized minimum variance controllers for nonlinear multivariable systems [PDF]
, 2006 The design and implementation of Generalized Minimum Variance control laws for nonlinear multivariable systems that can include severe nonlinearities is considered.
Grimble, Michael J.
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The Empirical Minimum‐Variance Hedge [PDF]
American Journal of Agricultural Economics, 1994 AbstractDecision making under unknown true parameters (estimation risk) is discussed along with Bayes' and parameter certainty equivalent (PCE) criteria. Bayes' criterion incorporates estimation risk in a manner consistent with expected utility maximization.
Hayes, Dermot, Lence, Sergio
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Robust minimum variance beamforming [PDF]
IEEE Transactions on Signal Processing, 2004 This paper introduces an extension of minimum variance beamforming that explicitly uses the a-priori uncertainty in the array response. Sources of this uncertainty include imprecise knowledge of the angle of arrival and uncertainty in the array manifold; this uncertainty is modeled via an ellipsoid.
Robert G. Lorenz, Stephen P. Boyd
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Polynomial approach to nonlinear predictive generalized minimum variance control [PDF]
, 2010 A relatively simple approach to non-linear predictive generalised minimum variance (NPGMV) control is introduced for non-linear discrete-time multivariable systems.
Majecki, P.M., Grimble, M.J.
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Application of futures in calculating optimal hedge ratio in crude oil market: Comparison between static and dynamic approaches [PDF]
مدلسازی اقتصادسنجی, 2020 Futures are used as the most important risk hedge tools to reduce the risk of the crude oil market. The optimal hedging risk strategy is determined by calculating the optimal hedging risk ratio.
Simin Aleali +3 more
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Novel Unbiased Optimal Receding-Horizon Fixed-Lag Smoothers for Linear Discrete Time-Varying Systems
Applied Sciences, 2022 This paper proposes novel unbiased minimum-variance receding-horizon fixed-lag (UMVRHF) smoothers in batch and recursive forms for linear discrete time-varying state space models in order to improve the computational efficiency and the estimation ...
Bokyu Kwon, Pyung Soo Kim
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