Title :
A research of FL neural network for fault diagnosis
Author :
Tianqi, Yang ; Zhan, Huang
Author_Institution :
Jinan Univ., Guangzhou, China
Abstract :
FL network architecture is a supervised learning extension of the BP network method we have studied thus far. It allows specification of the category into which inputs will be classified. In the designated category, the training set is extended into the input pattern of single layer perceptron with nonlinear change. It is high efficient in the aspects of processing speed and avoiding local stability, and especially useful in fault diagnosis
Keywords :
backpropagation; fault diagnosis; neural net architecture; perceptrons; BP network; FL network architecture; FL neural network; backpropagation; fault diagnosis; local stability avoidance; nonlinear change; single layer perceptron; supervised learning; Fault diagnosis; Inductors; Neural networks; Pi control; Stability; Supervised learning;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863417
