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The Hybrid LVQ Learning Algorithm for EMG Pattern Recognition

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2005, 10(2), pp.113-122
  • 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 hybrid learning algorithm of LVQ which is to perform EMG pattern recognition. The proposed hybrid LVQ learning algorithm is the modified Counter Propagation Networks(C.P. Net.) which is use SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of LVQ.The weights of the proposed C.P. Net. which is between input layer and subclass layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ algorithm, and pattern vectors is classified into subclasses by neurons which is being in the subclass layer, and the weights which is between subclass layer and class layer of C.P. Net. is learned to classify the classified subclass, which is enclosed a class. To classify the pattern vectors of EMG, the proposed algorithm is simulated with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional LVQ.

Citation status

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