optical coherence tomography (oct) uses the spatial and temporal coherence properties of optical waves backscattered from a tissue sample to form an image. an inherent characteristic of coherent imaging is the presence of speckle noise. in this study we use a new ensemble framework which is a combination of several multi-layer perceptron (mlp) neural networks to denoise oct images. the noise is...

Diierent predictors and their approximators in nonlinear prediction regression models are studied. The minimal value of the mean squared error (MSE) is derived. Some approximate formulae for the MSE of ordinary and weighted least squares predictors are given.

Different predictors and their approximators in nonlinear prediction regression models are studied. The minimal value of the mean squared error (MSE) is derived. Some approximate formulae for the MSE of ordinary and weighted least squares predictors are given.

This paper presents a density estimator based upon a histogram computed on a fuzzy partition. We prove the consistency of this estimator in the Mean Squared Error (MSE). We give the optimal bin width of the estimator which minimizes the Asymptotic Integrated Mean Squared Error (AIMSE). c © 2008 Elsevier B.V. All rights reserved.

Diierent predictors and their approximators in nonlinear prediction regression models are studied. The minimal value of the mean squared error (MSE) is derived. Some approximate formulae for the MSE of ordinary and weighted least squares predictors are given.

Abstract This note discusses some issues related to bandwidth selection based on moment expansions of the mean squared error (MSE) of the regression quantile estimator. We use higher order expansions to provide a way to distinguish among asymptotically equivalent nonparametric estimators. We derive approximations to the (standardized) MSE of the covariance matrix estimation. This facilitates a ...