Results 271 to 280 of about 4,152,384 (323)

Upper Error Bound Selection in Bounded Parameter Estimation

IFAC Proceedings Volumes, 1994
Abstract The problem of upper error bound selection in bounded parameter estimation for models linear-in-the-parameters is considered. It is shown that this selection implies a trade-off between posterior parametric and nonparametric uncertainty. A minimum uncertainty description of the model behaviour is obtained from min-max parameter estimation ...
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Sharp estimates for Hübner’s upper bound function with applications

Applied Mathematics-A Journal of Chinese Universities, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qiu, Songliang, Ren, Liangyu
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Extension of the Upper Bound Method to Include Estimation of Stresses

Journal of Applied Mechanics, 1991
The upper bound method is a convenient tool for evaluating the rate of work in processes involving predominantly plastic deformation of rigid/perfectly plastic material. Since the rate of work for an incompressible material depends only on the deviator portion of the stress, the hydrostatic portion does not enter the formulation and the stress field is
Azarkhin, A., Richmond, O.
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An upper bound on the estimation error in the threshold region

IEEE Transactions on Information Theory, 1970
Summary: An upper bound on the estimation error in the threshold region (probability of threshold effect and mean-square error) is obtained for nonlinear pulse modulation systems. The problem is viewed in an \(N\)-dimensional Euclidean space. The space of all received signals is divided into two regions, corresponding to the two types of error: weak ...
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Signal power upper bound in parameter estimation

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
In this note, an upper bound on the signal power corresponding to a hypothesized model is derived assuming unknown signal and noise characteristics. A residual matrix is obtained from the observed data correlation matrix by subtracting a weighted outer product of the model vector.
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Estimating the upper bound of transmission capacity in linear VANET

2015 International Wireless Communications and Mobile Computing Conference (IWCMC), 2015
The IEEE 802.11p VANET has been studied by academia and industry for many years. In this paper the upper bound of transmission capacity in linear VANET is deduced and evaluated. The maximum of simultaneous transmitters within dedicated areas, which is widely accepted as the indicator of transmission capacity, is constrained by the CSMA/CA or EDCA ...
Weisen Shi, Xinxin He, Tao Luo 0005, Lei Ding   +3 more
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Upper and Lower Estimates for the Modulus of Bounded Holomorphic Functions

Complex Analysis and Operator Theory, 2015
The following multi-point version of \textit{V. N. Dubinin}'s theorem [J. Math. Sci. 207, (6), 825--831 (2015)] is proved. Theorem. Let \(f\) be a holomorphic self-map of the unit disc \({\mathbb D}\), whose image does not contain any circle \(|z|=\rho ...
Cleanthous, Galatia, Georgiadis, Athanasios   +1 more
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Estimating Upper Bounds for Improving the Filtering in Interval Branch and Bound Optimizers

2014 IEEE 26th International Conference on Tools with Artificial Intelligence, 2014
When interval branch and bound solvers are used for solving constrained global optimization, upper bounding the objective function is an important mechanism which helps to reduce globally the search space. Each time a new upper bound UB is found during the search, a constraint related to the objective function fobj (x).
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Lower and upper bounds of the sizes of domains: Estimates and experiments

Information Processing Letters, 1986
Abstract We present a statistical method which allows computation of estimates of lower and upper bounds of the unknown sizes of domains on weaker assumptions than the usual ones. The results of experiments enable us to compare the computed bounds to the already known sizes of actual domains.
Paul Bourret, R. Souza de Oliveira
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An upper bound on average estimation error in nonlinear systems

IEEE Transactions on Information Theory, 1968
An upper bound is obtained on the probability density of the estimate of the parameter m when a nonlinear function s(t, m) is transmitted over a channel that adds Gaussian noise, and maximum likelihood or maximum a posteriori estimation is used. If this bound is integrated with a loss function, an upper bound on the average error is obtained. Nonlinear
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