• DocumentCode
    928362
  • Title

    A comparison between habituation and conscience mechanism in self-organizing maps

  • Author

    Rizzo, R. ; Chella, A.

  • Author_Institution
    Inst. di Calcolo e Reti ad Alte Prestazioni, ICAR-CNR, Palermo
  • Volume
    17
  • Issue
    3
  • fYear
    2006
  • fDate
    5/1/2006 12:00:00 AM
  • Firstpage
    807
  • Lastpage
    810
  • Abstract
    In this letter, a preliminary study of habituation in self-organizing networks is reported. The habituation model implemented allows us to obtain a faster learning process and better clustering performances. The habituable neuron is a generalization of the typical neuron and can be used in many self-organizing network models. The habituation mechanism is implemented in a SOM and the clustering performances of the network are compared to the conscience learning mechanism that follows roughly the same principle but is less sophisticated
  • Keywords
    learning (artificial intelligence); self-organising feature maps; conscience learning mechanism; habituable neuron; habituation model; self-organizing maps; Algorithm design and analysis; Instruction sets; Intelligent networks; Learning systems; Neurons; Nonhomogeneous media; Self organizing feature maps; Self-organizing networks; Unsupervised learning; Vector quantization; Conscience learning; habituation; self-organizing feature maps; unsupervised learning; Algorithms; Artificial Intelligence; Conscience; Habituation, Psychophysiologic; Information Storage and Retrieval; Neural Networks (Computer); Pattern Recognition, Automated; Systems Theory;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2006.872354
  • Filename
    1629103