DocumentCode
2663609
Title
A new method in incremental neural network construction by using boosting
Author
Wang, X. ; Brown, D. ; Haynes, B. ; Hui, T.M.J.
Author_Institution
Portsmouth Univ., UK
fYear
2003
fDate
4-6 Sept. 2003
Firstpage
173
Lastpage
177
Abstract
A weighted optimisation method based on the AdaBoost algorithm is proposed and used in neural network incremental construction. Compared to the traditional gradient-based method, it has the advantage of being easy to implement and are applied where the cost function is not smooth. The experimental results are included.
Keywords
Ada; Gaussian processes; approximation theory; learning (artificial intelligence); optimisation; radial basis function networks; signal processing; AdaBoost algorithm; Gaussian function network; incremental neural network construction; radial basis function network; weighted optimisation method; Boosting; Cost function; Intelligent networks; Kernel; Least squares approximation; Least squares methods; Neural networks; Neurons; Radial basis function networks; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Signal Processing, 2003 IEEE International Symposium on
Print_ISBN
0-7803-7864-4
Type
conf
DOI
10.1109/ISP.2003.1275834
Filename
1275834
Link To Document