Adaptive sliding mode approach for learning in a feedforward neural network

被引：32
|
作者：
Yu, X [1 ]
Zhihong, M
Rahman, SMM
机构：
[1] Univ Cent Queensland, Fac Informat & Commun, Rockhampton, Qld 4702, Australia
[2] Univ Tasmania, Dept Elect Engn & Comp Sci, Hobart, Tas, Australia
[3] Monash Univ, Dept Comp Sci & Software Engn, Clayton, Vic 3168, Australia
来源：
NEURAL COMPUTING & APPLICATIONS | 1998年 / 7卷 / 04期
关键词：
adaptive linear elements; back-propagation; sliding mode concept;
D O I：
10.1007/BF01428120
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An adaptive learning algorithm is proposed for a feedforward neural network The design principle is based on the sliding mode concept. Unlike the existing algorithms, the adaptive learning algorithm developed does not require a priori knowledge of upper bounds of bounded signals. The convergence of the algorithm is established and conditions given. Simulations are presented to show the effectiveness of the algorithm.
引用
收藏
页码：289 / 294
页数：6
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