• DocumentCode
    2777369
  • Title

    Chaotic Quaternionic Associative Memory

  • Author

    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 propose a chaotic quaternionic neuron model and a Chaotic Quaternionic Associative Memory (CQAM). The proposed chaotic quaternionic neuron model is based on the chaotic neuron model and the quaternionic neuron model. In the chaotic quaternionic neuron model, if the parameters are set appropriately, chaotic response can be generated. The proposed Chaotic Quaternionic Associative Memory is composed of chaotic quaternionic neuron models, and has a structure which is similar to the Hopfield network. In the proposed Chaotic Quaternionic Associative Memory, plural patterns are given to the network as external inputs at the same time, each pattern can be recalled separately. The proposed Chaotic Quaternionic Associative Memory makes use of the dynamic association ability of the chaotic quaternionic neuron model in order to realize pattern separation. We carried out a series of computer experiments and confirmed that (1) the chaotic quaternionic neuron can generate chaotic response when the parameters are set appropriately and (2) the pattern separation can be realized in the Chaotic Quaternionic Associative Memory.
  • Keywords
    Hopfield neural nets; chaos; content-addressable storage; number theory; CQAM; Hopfield network; chaotic quaternionic associative memory; chaotic quaternionic neuron model; chaotic response generation; dynamic association ability; pattern separation; Birds; Whales;
  • 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.2012.6252775
  • Filename
    6252775