|
|
|
|
|
Hai Huyen Dam and Sven Nordholm
This paper proposes a new adaptive algorithm for the second-order blind signal separation (BSS) problem with convolutive mixtures by utilising a combination of an accelerated gradient and a conjugate gradient method. For each iteration of the adaptive al...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kemal Güven and Andaç Töre Samiloglu
Neural networks are one of the methods used in system identification problems. In this study, a NARX network with a serial-parallel structure was used to identify an unknown aerial delivery system with a ram-air parachute. The dataset was created using t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Raúl Ulices Silva-Ávalos, Hugo Enrique Júnez-Ferreira, Julián González-Trinidad and Carlos Bautista-Capetillo
In Mexico, agriculture in semi-arid regions is highly dependent on groundwater resources, where most of the aquifers? characterization is a pending task. In particular, the depth to the basement is unknown for most of the Mexican territory. Hence, the de...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zabidin Salleh, Ghaliah Alhamzi, Ibitsam Masmali and Ahmad Alhawarat
The conjugate gradient method is one of the most popular methods to solve large-scale unconstrained optimization problems since it does not require the second derivative, such as Newton?s method or approximations. Moreover, the conjugate gradient method ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Farzad Mohebbi
Explicit expressions are obtained for sensitivity coefficients to separately estimate temperature-dependent thermophysical properties, such as specific heat and thermal conductivity, in two-dimensional inverse transient heat conduction problems for bodie...
ver más
|
|
|
|
|
|
|
|
|
|
|
Luca Bergamaschi
The aim of this survey is to review some recent developments in devising efficient preconditioners for sequences of symmetric positive definite (SPD) linear systems ????????=????,??=1,?
A
k
x
k
=
b
k
,
k
=
1
,
?
arising in many scientific applications, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yanfeng Zhang, Yunbao Huang, Haiyan Li, Pu Li and Xi?an Fan
We propose a new iterative greedy algorithm to reconstruct sparse signals in Compressed Sensing. The algorithm, called Conjugate Gradient Hard Thresholding Pursuit (CGHTP), is a simple combination of Hard Thresholding Pursuit (HTP) and Conjugate Gradient...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiuyun Zheng and Jiarong Shi
In this paper, a modification to the Polak?Ribiére?Polyak (PRP) nonlinear conjugate gradient method is presented. The proposed method always generates a sufficient descent direction independent of the accuracy of the line search and the convexity of the ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sungwon Kim and Vijay P. Singh
The objective of this study is to develop artificial neural network (ANN) models, including multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial disaggregation of areal rainfall in the Wi-stream catchment, an Internati...
ver más
|
|
|
|
|
|
|
|
|
|
|
Saghir Ahmad and Laiq Khan
The existing literature predominantly concentrates on the utilization of the gradient descent algorithm for control systems? design in power systems for stability enhancement. In this paper, various flavors of the Conjugate Gradient (CG) algorithm have b...
ver más
|
|
|
|
|
|
|
|
|
|
|
Miglena N. Koleva and Lubin G. Vulkov
The retrospective inverse problem for evolution equations is formulated as the reconstruction of unknown initial data by a given solution at the final time. We consider the inverse retrospective problem for a one-dimensional parabolic equation in two dis...
ver más
|
|
|
|
|
|
|
|
|
|
|
Marcele O. K. Mendonça, Jonathas O. Ferreira, Christos G. Tsinos, Paulo S R Diniz and Tadeu N. Ferreira
The amount of information currently generated in the world has been increasing exponentially, raising the question of whether all acquired data is relevant for the learning algorithm process. If a subset of the data does not bring enough innovation, data...
ver más
|
|
|
|
|
|
|
|
|
|
|
Marcele O. K. Mendonça, Jonathas O. Ferreira, Christos G. Tsinos, Paulo S R Diniz and Tadeu N. Ferreira
The amount of information currently generated in the world has been increasing exponentially, raising the question of whether all acquired data is relevant for the learning algorithm process. If a subset of the data does not bring enough innovation, data...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mustafa Arif Özgür
Wind energy is one of the most signi?cant and rapidly developing renewable energy sources in the world and it provides a clean energy resource, which is a promising alternative in the short term in Turkey. The wind energy potential in various parts of Tu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dmitry Lukyanenko, Valentin Shinkarev and Anatoly Yagola
This paper discusses a method for taking into account rounding errors when constructing a stopping criterion for the iterative process in gradient minimization methods. The main aim of this work was to develop methods for improving the quality of the sol...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xenofon Trompoukis, Konstantinos Tsiakas, Varvara Asouti, Marina Kontou and Kyriakos Giannakoglou
This paper presents an adjoint-based shape optimization framework and its demonstration in a conjugate heat transfer problem in a turbine blading. The gradient of the objective function is computed based on the continuous adjoint method, which also inclu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alberto Racca, Tom Verstraete and Lorenzo Casalino
This paper addresses the problem of the design optimization of turbomachinery components under thermo-mechanical constraints, with focus on a radial turbine impeller for turbocharger applications. Typically, turbine components operate at high temperature...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kyoum Sun Kim and Jae Heon Yun
In this paper, we first propose a new TVL2 regularization model for image restoration, and then we propose two iterative methods, which are fixed-point and fixed-point-like methods, using CGLS (Conjugate Gradient Least Squares method) for solving the new...
ver más
|
|
|
|
|
|
|
|
|
|
|
Vladimir Krutikov, Elena Tovbis, Anatoly Bykov, Predrag Stanimirovic, Ekaterina Chernova and Lev Kazakovtsev
We investigate a solution of a convex programming problem with a strongly convex objective function based on the dual approach. A dual optimization problem has constraints on the positivity of variables. We study the methods and properties of transformat...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chao Wang, Jianhui Xu, Yuefeng Li, Tuanhui Wang and Qiwei Wang
Rockbursts are serious threats to the safe production of mining, resulting in great casualties and property losses. The accurate prediction of rockburst is an important premise that influences the safety and health of miners. As a classical machine learn...
ver más
|
|
|
|
|
|