Results 261 to 270 of about 190,116 (291)

An iterative approach to minimize the mean squared error in ridge regression

Computational Statistics, 2015
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Wong, Ka Yiu, Chiu, Sung Nok
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Error Entropy and Mean Square Error Minimization Algorithms for Neural Identification of Supercritical Extraction Process

2008 10th Brazilian Symposium on Neural Networks, 2008
In this paper, artificial neural networks (ANN) are used to model an extraction process that uses a supercritical fluid as solvent which its pilot installation is located at the Institute of Experimental and Technological Biology - IBET in Oeiras - Lisbon - Portugal.
Rosana Paula de Oliveira Soares, Adriana Rosa Garcez Castro, Roberto Célio Limão de Oliveira, Vladimiro Miranda   +3 more
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PtNLMS algorithm obtained by minimization of mean square error modeled by exponential functions

2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, 2010
Using the proportionate-type steepest descent algorithm we represent the current weight deviations in terms of initial weight deviations. Then we attempt to minimize the mean square output error with respect to the gains at a given instant. The corresponding optimal average gains are found using a water-filling procedure.
Kevin T. Wagner, Milos I. Doroslovacki
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Linear model averaging by minimizing mean-squared forecast error unbiased estimator

Model Assisted Statistics and Applications, 2016
This paper presents a new ordinary least squares model averaging method which is proposed to be a preferable alternative to Mallows Model Averaging (MMA), Bayesian Model Averaging (BMA) and naïve simple forecast average. The method is developed to deal with possibly non-nested models and selects forecast weights by minimizing the unbiased estimator of ...
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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
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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
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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 ...
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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
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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
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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.
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