ARTÍCULO
TITULO

Parallel Nonlinear Optimization Techniques for Training Neural Networks

Phua    
P. K. H. Ming    
D.    

Resumen

No disponible

PÁGINAS
pp. 1460 - 1468

 Artículos similares

       
 
Long Chen, Diju Gao and Qimeng Xue    
Reducing energy consumption and carbon emissions from ships is a major concern. The development of hybrid technologies offers a new direction for the rational distribution of energy. Therefore, this paper establishes a torque model for internal combustio... ver más

 
Soo-Min Kim, Dae W. Kim and Moon K. Kwak    
The membrane-type air spring can be used to suppress lateral vibration of a vibration isolation table. However, compared to voice coil actuators, pneumatic actuators are difficult to use for precise vibration control, because servo valves have nonlinear ... ver más
Revista: Applied Sciences

 
Weidong Wu, Hongbo Fan, Yu Fan and Jian Wen    
The accurate segmentation of colorectal polyps is of great significance for the diagnosis and treatment of colorectal cancer. However, the segmentation of colorectal polyps faces complex problems such as low contrast in the peripheral region of salient i... ver más
Revista: Information

 
Gérard Favier and Alain Kibangou    
Nonlinear (NL) and multilinear (ML) systems play a fundamental role in engineering and science. Over the last two decades, active research has been carried out on exploiting the intrinsically multilinear structure of input?output signals and/or models in... ver más
Revista: Algorithms

 
Yidong Chen, Chen Li and Zhonghua Lu    
In this paper, we propose a parallel algorithm for a fund of fund (FOF) optimization model. Based on the structure of objective function, we create an augmented Lagrangian function and separate the quadratic term from the nonlinear term by the alternate ... ver más
Revista: Algorithms