Results 261 to 270 of about 189,088 (295)

An optimal pointwise weighted ensemble of surrogates based on minimization of local mean square error

Structural and Multidisciplinary Optimization, 2020
Surrogate models are often used as surrogates for computationally intensive simulations. And there are a variety of surrogate models which are widely used in aerospace engineering–related investigation and design. In general, there is an optimal individual surrogate for a certain research object.
Yifan Ye, Zhanxue Wang, Xiaobo Zhang
openaire   +1 more source

Filter Bank Design for Minimizing Mean-Squared Estimation Error in Subband Adaptive Filtering

Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005., 2006
This paper considers the problem of prototype filter design for subband adaptive filtering applied to system identification. The minimum mean-squared estimation error (MMSE) depends only the subband analysis filter and the response of the unknown system. We use MMSE as a design criterion to select the best analysis filter response. We show how this can
J. Gunther, T. Bose, W. Song
openaire   +1 more source

Robust Least-Squares Support Vector Machine With Minimization of Mean and Variance of Modeling Error

IEEE Transactions on Neural Networks and Learning Systems, 2017
The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers.
Xinjiang Lu, Wenbo Liu, Chuang Zhou, Minghui Huang   +3 more
openaire   +2 more sources

Minimizing average mean squared error: a comparison of preliminary test estimation to other procedures

Journal of Statistical Computation and Simulation, 1978
The approach of preliminary test estimation has been suggested by Ellerton and Myers (1977) as a means for controlling the size of the J-criterion of the estimator ŷ of the true response,ηIn this paper, the j-criterion associated with the response estimator employed by Ellerton and Myers is evaluated and comparisons made with the j-criteria of several ...
Thomas B. Vassar, Walter H. Carter
openaire   +1 more source

A New Estimator of the Variance Based on Minimizing Mean Squared Error

The American Statistician, 2012
In 2005, Yatracos constructed the estimator S 2 2 = c 2 S 2, c 2 = (n + 2)(n − 1)[n(n + 1)]− 1, of the variance, which has smaller mean squared error (MSE) than the unbiased estimator S 2. In this work, the estimator S 2 1 = c 1 S 2, c 1 = n(n − 1)[n(n − 1) + 2]− 1, is constructed and is shown to have the following properties: (a) it has smaller MSE ...
openaire   +1 more source

A new histogram-based estimation technique of entropy and mutual information using mean squared error minimization

Computers & Electrical Engineering, 2013
Mutual Information (MI) has extensively been used as a measure of similarity or dependence between random variables (or parameters) in different signal and image processing applications. However, MI estimation techniques are known to exhibit a large bias, a high Mean Squared Error (MSE), and can computationally be very costly.
Hacine-Gharbi, Abdenour, Deriche, Mohamed, Ravier, Philippe, Harba, Rachid, Mohamadi, Tayeb   +4 more
openaire   +2 more sources

Optimum reference node deployment for indoor localization based on the average Mean Square Error minimization

2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC), 2015
Using the Global Positioning System (GPS) for indoor localization is challenging as the GPS signal is significantly attenuated or completely blocked by the building. In achieving indoor localization, a set of transmitters from wireless communication networks are often used as reference nodes to localize target nodes with unknown locations. The accuracy
null Fei Long, Aydin Behnad, null Xianbin Wang   +2 more
openaire   +1 more source

Designs in nonlinear regression by stochastic minimization of functionals of the mean square error matrix

Journal of Statistical Planning and Inference, 2006
We reconsider and extend the method of designing nonlinear experiments presented in Pázman and Pronzato (J. Statist. Plann. Inference 33 (1992) 385). The approach is based on the probability density of the LS estimators, and takes into account the boundary of the parameter space. The idea is to express the elements of the mean square error matrix (MSE)
Gauchi, Jean-Pierre, Pázman, A.
openaire   +3 more sources

A binning formula of bi-histogram for joint entropy estimation using mean square error minimization

Pattern Recognition Letters, 2018
Abstract Histograms have extensively been used as a simple tool for nonparametric probability density function estimation. However, practically, the accuracy of some histogram-based derived quantities, such as the marginal entropy (ME), the joint entropy (JE), or the mutual information (MI) depends on the number of bins chosen for the histogram.
Hacine-Gharbi, Abdenour, Ravier, Philippe   +1 more
openaire   +1 more source

High-capacity data hiding in halftone images using minimal-error bit searching and least-mean square filter

IEEE Transactions on Image Processing, 2006
In this paper, a high-capacity data hiding is proposed for embedding a large amount of information into halftone images. The embedded watermark can be distributed into several error-diffused images with the proposed minimal-error bit-searching technique (MEBS).
Pei, Soo-Chang, Guo, Jing-Ming
openaire   +2 more sources