J4 ›› 2009, Vol. 27 ›› Issue (05): 514-.

Previous Articles     Next Articles

Approach to Eliminating Morbid Samples in Forward Neural Networks

LI Chun-hao1, LIU Cheng-ming1,CAI Gan2
  

  1. 1.School of Management, Jilin University, Changchun 130025, China;2. Shenzhen Huaming Computer LTD, Shenzhen 518035, China
  • Online:2009-09-20 Published:2009-11-03

Abstract:

For efficiently eliminating morbid samples and improving the generalization ability of neural networks, we present an approach to eliminate morbid samples in forward neural networks based on the search thought and the Hamming distance, through developing the thought and introducing the distance. The approach can directly carry out searching and eliminating morbid samples, and do not consider prior knowledge, forms of samples, etc. Hence, its applicability is stronger. The results of numerical demonstration analysis show that the approach is scientific, effective and can effectively find out morbid samples of learning samples,it has obvious application value to solve problems of real world.

Key words: forward neural network, morbid sample, eliminate, search, hamming distance

CLC Number: 

  • TP18