• DocumentCode
    3495374
  • Title

    Chaotic Complex-valued Multidirectional Associative Memory with variable scaling factor - One-to-many association ability -

  • Author

    Yoshida, Akio ; Osana, Yuko

  • Author_Institution
    Sch. of Comput. Sci., Tokyo Univ. of Technol., Hachioji, Japan
  • fYear
    2011
  • fDate
    July 31 2011-Aug. 5 2011
  • Firstpage
    1285
  • Lastpage
    1292
  • Abstract
    In this paper, we propose a Chaotic Complex-valued Multidirectional Associative Memory (CCMAM) with variable scale factor which can realize one-to-many associations of M-tuple multi-valued patterns. The proposed model is based on the Multidirectional Associative Memory, and is composed of complex-valued neurons and chaotic complex-valued neurons. In the proposed model, associations of multivalued patterns are realized by using complex-valued neurons, and one-to-many associations are realized by using chaotic complex-valued neurons. Moreover, in the proposed model, the appropriate parameters of chaotic complex-valued neurons can be determined easily than in the original Chaotic Complex-valued Multidirectional Associative Memory. We carried out a series of computer experiments and confirmed that the proposed model has superior one-to-many association ability than that of the conventional model.
  • Keywords
    chaos; content-addressable storage; neural nets; M-tuple multivalued patterns; chaotic complex-valued multidirectional associative memory; chaotic complex-valued neurons; complex-valued neurons; information processing; neural networks; one-to-many association ability; variable scaling factor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2011 International Joint Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4244-9635-8
  • Type

    conf

  • DOI
    10.1109/IJCNN.2011.6033372
  • Filename
    6033372