본문 바로가기
  • Home

3 steps LVQ Learning algorithm using Forward C.P Net.

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2004, 9(4), pp.33-39
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Lee Yong Gu 1 CHOI , WOO SEUNG 2

1한림성심대학교
2경원대학교

Candidate

ABSTRACT

In this paper, we design the learning algorithm of LVQ which is used Forward Counter Propagation Networks to improve classification performance of LVQ networks. The weights of Forward Counter Propagation Networks which is between input layer and cluster layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ algorithm. Finally, pattern vectors is classified into subclasses by neurons which is being in the cluster layer, and the weights of Forward Counter Propagation Networks which is between cluster layer and output layer is learned to classify the classified subclass, which is enclosed a class. Also, if the number of classes is determined, the number of neurons which is being in the input layer, cluster layer and output layer can be determined. To prove the performance of the proposed learning algorithm, the simulation is performed by using training vectors and test vectors that are Fisher's Iris data, and classification performance of the proposed learning method is compared with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional classification.

Citation status

* References for papers published after 2022 are currently being built.