English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51258/86283 (59%)
Visitors : 8007214      Online Users : 60
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46121


    Title: A neural-network-based approach to detecting hyperellipsoidal shells
    Authors: 蘇木春;Su, Mu-chun;Liu, I-chen
    Contributors: 淡江大學電機工程學系
    Keywords: cluster analysis;neural networks;shell detection
    Date: 1999-06
    Issue Date: 2010-03-26 20:59:49 (UTC+8)
    Publisher: Springer
    Abstract: This paper presents a novel class of neural networks which can be trained in an unsupervised manner to detect a mixture of hyperellipsoidal shells and/or segments of hyperellipsoidal shells. This approach is computationally and implementationally simpler than other clustering algorithms that have been suggested for this purpose. Experimental results on several data sets are presented.
    Relation: Neural Processing Letters 9(3), pp.279-292
    DOI: 10.1023/A:1018676508833
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

    Files in This Item:

    File SizeFormat
    0KbUnknown241View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback