Feed-forward Learning Algorithm by Generalized Clustering Network 


Vol. 2,  No. 5, pp. 619-625, Sep.  1995
10.3745/KIPSTE.1995.2.5.619


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  Abstract

This paper constructs a feed-forward learning complex algorithm which replaced by the backpropagation learning. This algorithm first attempts to organize the pattern vectors into clusters by Generalized Learning Vector Quantization(GLVQ) clustering algorithm(Nikhil R. Pal et al, 1993), second, regroup the pattern vectors belonging to different clusters, and the last, recognize into regrouping pattern vectors by single layer perceptron. Because this algorithm is feed-forward learning algorithm, total learning time is less than backpropagation algorithm and the recognition rate is increased. We use 250 ASCII code bit patterns that is normalized to 16 X 8. As experimental results, when 250 patterns devide by 10 clusters, average iteration of each cluster is 94.7, and recognition rate is 100%.,

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[IEEE Style]

M. J. Young and C. H. Ki, "Feed-forward Learning Algorithm by Generalized Clustering Network," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 2, no. 5, pp. 619-625, 1995. DOI: 10.3745/KIPSTE.1995.2.5.619.

[ACM Style]

Min Joon Young and Cho Hyung Ki. 1995. Feed-forward Learning Algorithm by Generalized Clustering Network. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 2, 5, (1995), 619-625. DOI: 10.3745/KIPSTE.1995.2.5.619.

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