• DocumentCode
    3100170
  • Title

    Batch implementation of Growing Self-Organizing Map

  • Author

    Yu, Yaohua ; Alahakoon, Damminda

  • Author_Institution
    Clayton Sch. of Inf. Technol., Monash Univ., Clayton, VIC
  • fYear
    2006
  • fDate
    Nov. 28 2006-Dec. 1 2006
  • Firstpage
    162
  • Lastpage
    162
  • Abstract
    The growing self-organizing map algorithm (GSOM) has been developed based on SOM. With its dynamic structure, GSOM can generate feature maps without pre-determining their size. It has shown many significant advantages when processing very large data sets. These advantages could be further enhanced if the processing speed of the algorithm could be increased. This paper presents a modified version of GSOM, which implements the batch processing principle to shorten the processing time. The algorithm and experimental results showing the improved performance are presented in this paper.
  • Keywords
    batch processing (computers); self-organising feature maps; batch implementation; dynamic structure; growing self-organizing map; Automatic generation control; Clustering algorithms; Computational intelligence; Computational modeling; Educational institutions; Information technology; Probability density function; Size control; Space technology; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    0-7695-2731-0
  • Type

    conf

  • DOI
    10.1109/CIMCA.2006.58
  • Filename
    4052790