Title :
An Accelerating Method of Training Neural Networks Based on Vector Epsilon Algorithm
Author :
Li, Jianliang ; Lian, Lian ; Jiang, Yong
Author_Institution :
Sch. of Sci., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
This paper studied the accelerating convergence of the vector sequences generated by BP algorithm with vector epsilon algorithm, and presented the conclusion that the algorithms is not only convergent but also accelerated. Finally, we tested them for three classical artificial neural network problems. By numerical experiments, results shown that can reduce CPU time for computation and improve the learning efficiency.
Keywords :
backpropagation; convergence; feedforward neural nets; learning (artificial intelligence); sequences; vectors; BP algorithm; CPU; accelerating convergence; artificial neural network; computation time; vector epsilon algorithm; vector sequence; Acceleration; Artificial neural networks; Computer networks; Feedforward neural networks; Feedforward systems; Feeds; Gradient methods; Iterative algorithms; Multi-layer neural network; Neural networks; BP algorithm; accelerated convergence; artificial neural networks; epsilon algorithm; numerical analysis;
Conference_Titel :
Information and Computing (ICIC), 2010 Third International Conference on
Conference_Location :
Wuxi, Jiang Su
Print_ISBN :
978-1-4244-7081-5
Electronic_ISBN :
978-1-4244-7082-2
DOI :
10.1109/ICIC.2010.345
