模式识别与人工智能
Tuesday, Jul. 29, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
  2006, Vol. 19 Issue (2): 220-226    DOI:
Researches and Applications Current Issue| Next Issue| Archive| Adv Search |
An Improvement of the RAN Learning Algorithm
LI Bin
School of Information Engineering, Shandong University at Weihai, Weihai 264209
College of Mathematical and Physical Sciences, Shandong Institute of Light Industry, Jinan 250100

Download: PDF (1304 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  An improved learning algorithm for Resource Allocating Network (RAN) is presented in this paper, which is called IRAN algorithm. It allocates hidden neurons of network by a fourpart novelty criterion, removes redundant neurons according to their error reduction rates, and updates outputlayer weights by a recursive leastsquares algorithm with GivensQR decomposition. Simulations on two Benchmark problems in the function approximation area indicate that the IRAN algorithm can provide smaller networks and consume less training time than RAN, RANEKF and MRAN algorithms.
Key wordsResource Allocating Network (RAN) Learning Algorithm      Radial Basis Function      Hidden Neurons      GivensQR Decomposition      Pruning Strategy     
Received: 14 October 2004     
ZTFLH: TP183  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
LI Bin
Cite this article:   
LI Bin. An Improvement of the RAN Learning Algorithm[J]. , 2006, 19(2): 220-226.
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2006/V19/I2/220
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn