• DocumentCode
    2777379
  • Title

    Pattern dependency of one-to-many association ability in Chaotic Complex-valued Multidirectional Associative Memory with variable scaling factor

  • Author

    Onagi, Motoyuki ; Osana, Yuko

  • Author_Institution
    Sch. of Comput. Sci., Tokyo Univ. of Technol., Tokyo, Japan
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper, we examine the pattern dependency of the one-to-many association ability in the Chaotic Complex-valued Multidirectional Associative Memory (CCMAM) with variable scaling factor. The CCMAM is composed of complex-valued neurons and chaotic complex-valued neurons, and can realize one-to-many associations of M-tuple multi-valued patterns. The one-to-many association ability of the CCMAM depends the parameters of chaotic complex-valued neurons, and we have already examined the parameter dependency of the one-to-many association ability of this model, and confirmed that the scaling factor of the refractoriness in chaotic complex-valued neurons has a significant influence on the association ability. Although it is thought that stored patterns also have influence on the association ability, the pattern dependency of the one-to-many association ability in the CCMAM has not been examined. In this research, we examined the pattern dependency of the one-to-many association ability and confirmed that the one-to-many association ability decreases when the number of stored patterns or the number of stored common patterns are large.
  • Keywords
    chaos; content-addressable storage; M-tuple multivalued patterns; chaotic complex-valued multidirectional associative memory; chaotic complex-valued neuron refractoriness; one-to-many association ability; pattern dependency; variable scaling factor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2012 International Joint Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-1488-6
  • Electronic_ISBN
    2161-4393
  • Type

    conf

  • DOI
    10.1109/IJCNN.2012.6252776
  • Filename
    6252776