Estimation of variance components by Monte Carlo (MC) expectation maximization (EM) restricted maximum likelihood (REML) is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type ...

In this paper, Field-Programmable Gate Array (FPGA) implementation-based image demosaicing is carried out. The Newton Gregory interpolation algorithm designed based on FPGA frame work. Interpolation the method of assessing value a function for any in-between self-regulating variable, whereas computing outside specified range named extrapolation. natural images are collected from Kodak database ...

In this paper, we propose a new method for finding global optimum of continuous optimization problems, namely Level-Value Estimation algorithm(LVEM). First we define the variance function v(c) and the mean deviation function m(c) with respect to a single variable (the level value c), and both of these functions depend on the optimized function f(x). We verify these functions have some good prop...

In this paper, we consider both local and global convergence of the Newton algorithm to solve nonlinear problems when GMRES is used to invert the Jacobian at each Newton iteration. Under weak assumptions, we give a suucient condition for an inexact solution of GMRES to be a descent direction in order to apply a backtracking technique. Moreover, we extend this result to a nite diierence scheme c...