Title :
Fast Terminal Attractor Based Backpropagation Algorithm For Feedforward Neural Networks
Author :
Batbayar, Batsukh ; Yu, Xinghuo
Author_Institution :
R. Melbourne Inst. of Technol., Melbourne
Abstract :
In this paper, a new efficient fast terminal attractor based backpropagation learning algorithm for feedforward neural networks is proposed, which improves the convergence speed. The effectiveness of the proposed algorithm in improving learning speed is shown by the simulation results including a sensor network example.
Keywords :
backpropagation; feedforward neural nets; backpropagation learning; convergence speed; fast terminal attractor; feedforward neural networks; learning speed; Australia; Backpropagation algorithms; Computational modeling; Computer networks; Convergence; Data mining; Feedforward neural networks; Function approximation; Neural networks; Pattern recognition;
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information, 2007. ISSNIP 2007. 3rd International Conference on
Conference_Location :
Melbourne, Qld.
Print_ISBN :
978-1-4244-1501-4
Electronic_ISBN :
978-1-4244-1502-1
DOI :
10.1109/ISSNIP.2007.4496897
