Results 41 to 50 of about 124,946 (301)

Newton's Method [PDF]

, 2013
textRoot-finding algorithms have been studied for ages for their various applications. Newton's Method is just one of these root-finding algorithms.
Banacka, Nicole Lynn
core  

Learning regularized Gauss-Newton methods

, 2022
We consider variational networks for a class of nonlinear-ill-posed least squares inverse problems. These problems are addressed by regularized Gauss-Newton type optimization algorithms where the regularization is learned by a neural network.
Francesco Colibazzi, Andrea Samorè, Damiana Lazzaro, Serena Morigi   +3 more
core  

In‐Process Magnetization for 3D Printing of Magnetorheological Elastomer with Heterogeneous Magnetic Profile for Anisotropic Actuation

Advanced Science, EarlyView.
Fully programmable, in‐process 3D magnetization integrated with multi‐material printing enables soft magnetic systems with precise actuation and sensing. Discrete and continuous magnetization profiles drive bending, morphing, and locomotion, demonstrated through strain‐sensing elements, dragonfly‐inspired wings, octopus‐like tentacles, and a serpentine
Phillip Glass, David Hassouna, Udena Epitawala Arachchige, Hyeon Yun Jeong, Sung Hyun Park, Daeha Joung   +5 more
wiley   +1 more source

The Hybrid BFGS-CG Method in Solving Unconstrained Optimization Problems

Abstract and Applied Analysis, 2014
In solving large scale problems, the quasi-Newton method is known as the most efficient method in solving unconstrained optimization problems. Hence, a new hybrid method, known as the BFGS-CG method, has been created based on these properties, combining ...
Mohd Asrul Hery Ibrahim, Mustafa Mamat, Wah June Leong   +2 more
doaj   +1 more source

A Modified q-BFGS Algorithm for Unconstrained Optimization

Mathematics, 2023
This paper presents a modification of the q-BFGS method for nonlinear unconstrained optimization problems. For this modification, we use a simple symmetric positive definite matrix and propose a new q-quasi-Newton equation, which is close to the ordinary
Kin Keung Lai, Shashi Kant Mishra, Ravina Sharma, Manjari Sharma, Bhagwat Ram   +4 more
doaj   +1 more source

Machine‐Learning‐Enhanced Printed Vertical Magnetoresistive Sensors for Transparent, Flexible, Multimodal Interactive Magnetoelectronics

Advanced Science, EarlyView.
This study presents printed magnetoresistive sensors with a vertically aligned architecture that enables high optical transparency and mechanical flexibility. By integrating deep learning for the analysis of complex spatiotemporal signal patterns, the system further achieves intelligent multimodal interaction capabilities.
Rui Xu, Guannan Mu, Oleksandr V. Pylypovskyi, Qihao Zhang, Rico Illing, René Hübner, Ran He, Andreas Knüpfer, Sebastian Lehmann, Olha Bezsmertna, Kornelius Nielsch, Denys Makarov   +11 more
wiley   +1 more source

Métodos de Krylov-Newton aplicados à simulação numérica de reservatórios de petróleo [PDF]

, 2000
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico.A simulação do processo de extração de óleo em um reservatório de petróleo é um problema complexo que envolve o escoamento multifásico em um meio poroso de geometria ...
Lucianetti, Rodrigo Machado
core  

A Wave Digital Hierarchical Quasi-Newton Method for Virtual Analog Modeling

, 2022
LAUREA MAGISTRALEUn nuovo metodo, basato su un risolutore Newton-Raphson (NR) nel dominio dei Filtri Digitali ad Onda Numerica (Wave Digital), è stato recentemente proposto per l'emulazione digitale di circuiti analogici.
GOBBATO, LUCA
core  

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

An Adaptive Lp Norm Minimization Algorithm for Direction of Arrival Estimation

Remote Sensing, 2022
In this paper, we propose a new direction of arrival (DOA) estimation algorithm, in which DOA estimation is achieved by finding the sparsest support set of multiple measurement vectors (MMV) in an over-complete dictionary. The proposed algorithm is based
Lutao Liu, Zejing Rao
doaj   +1 more source