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Mustafa, F. Chen, J. Deng, Estimating error bounds for binary subdivision curves/surfaces, J. Comput.
An MKDA-based ordinal regression method for estimating error degrees in numerical weather prediction was presented in this paper.
In this paper, we will focus on the use of Fourier inversion approach and its use for estimating error probability.
This paper is devoted to estimating error bounds between the limit curve and the control polygon defined after k subdivision stages.
Our main objectives include finding some general and relatively simple ways for estimating error performance and demonstrating the trade-off of using cooperative relay processing.
Details on the procedures for estimating error and filtering extreme growth rates are given in Condit (1998b) and Condit et al. (2004).
Similar(41)
The estimating errors when using UKF and EKF are compared.
Resampling methodology, as mentioned above in generating ensemble classifiers, can be used for estimating errors.
It can be seen that the estimating errors of all the methods improve as N increases.
(b) performance of the angle estimation of the target 2. (c) 3D coordinates estimate error.
This method has rapid astringency of estimated error.
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