We propose an Adaptive Stochastic Conjugate Gradient (ASCG) optimization algorithm for temporal medical image registration. This method combines the advantages of Conjugate Gradient (CG) method and Adaptive Stochastic Gradient Descent (ASGD) method. The main idea is that the search direction of ASGD is replaced by stochastic approximations of the conjugate gradient of the cost function. In addi...

In this paper we suggest a new conjugate gradient algorithm that for all both the descent and the conjugacy conditions are guaranteed. The search direction is selected as a linear combination of 0 k ≥ 1 k g + − and where , k s 1 1 ( ) k k g f x + + = ∇ , and the coefficients in this linear combination are selected in such a way that both the descent and the conjugacy condition are satisfied at ...

Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based ...

The hybrid conjugate gradient (CG) method is among the efficient variants of CG for solving optimization problems. This due to their low memory requirements and nice convergence properties. In this paper, we present an unconstrained models show that satisfies sufficient descent condition. global prove proposed would be established under inexact line search. Application famous statistical regres...

This paper reports the study results on neural network training algorithm of numerical optimization techniques multiface detection in static images. The training algorithms involved are scale gradient conjugate backpropagation, conjugate gradient backpropagation with Polak-Riebre updates, conjugate gradient backpropagation with Fletcher-Reeves updates, one secant backpropagation and resilent ba...