Determination of Heat Convection Coefficent in Solidification Process Using conjugate Gradient Method....

In order to achieve a theoretically effective and numerically efficient method for solving large-scale unconstrained optimization problems, a hybridization of the Fletcher-Reeves and Polak-Ribière-Polyak conjugate gradient methods is proposed...

In this paper, we propose a three{term PRP{type conjugate gradient

method which always satisfies the sufficient descent condition independently of line

searches employed. An important property of our method ...

One of the most significant issues in machine learning is system identification with many applications, e.g., channel estimation (CE) in digital communications. Introducing a new correntropy-based method, this paper deals ...

simultaneously. Both of these parameters are considered as

functions of time, and since no information exists about their

functional form, the problem is classified as the function

estimation method. Conjugate gradient method...

Two adaptive choices for the parameter of Dai–Liao conjugate gradient (CG) method are suggested. One of which is obtained by minimizing the distance between search directions of Dai–Liao method and a three-term CG method ...

time, and since no information exists about their functional form, the problem is classified as the

function estimation approach. Conjugate gradient method is applied as an inverse method. Two test

cases are considered and the effect of measurement...

Based on an eigenvalue analysis, a descent class of two-parameter extension of the conjugate gradient method proposed by Polak and Ribière (1969), and Polyak (1969) is suggested.It is interesting that the one-parameter class of descent conjugate...

Hybridizing self-adjusting approach of Dong et al. and three-term formulation of Zhang et al., a nonlinear conjugate gradient method is proposed. The method reduces to the Polak–Ribière–Polyak method under the exact line search and satisfies...

Symmetrizing the Dai–Liao (DL) search direction matrix by a rank-one modification, we propose a one-parameter class of nonlinear conjugate gradient (CG) methods which includes the memoryless Broyden–Fletcher–Goldfarb–Shanno ...