• DocumentCode
    2708872
  • Title

    Design of unsupervised classifier

  • Author

    Sayeh, M.R. ; Ragu, A. ; Szu, H.H.

  • Author_Institution
    Dept. of Electr. Eng., Southern Illinois Univ., Carbondale, IL, USA
  • fYear
    1991
  • fDate
    8-14 Jul 1991
  • Firstpage
    417
  • Abstract
    Reports a feedback unsupervised classifier formulated by differential equations with no external control and few tuning parameters. This classifier is called the Lyapunov associative memory, in order to emphasize the importance of the Lyapunov (energy) function in the design of the associative memory. A vigilance parameter is built in to the dynamics of the classifier. Its architecture consists of two modules: the learning and recall modules. The learning module shapes the recall module, energy function with the arrival of new input information. The classifier was tested with an analog input pattern used by the ART-2 (adaptive resonance theory) model
  • Keywords
    Lyapunov methods; classification; content-addressable storage; differential equations; feedback; learning systems; neural nets; pattern recognition; ART-2; Lyapunov associative memory; adaptive resonance theory; analog input pattern; differential equations; dynamics; energy function; feedback unsupervised classifier; learning module; recall module; vigilance parameter; Associative memory; Equations; Feedback; Magnesium compounds; Shape; Silver; Springs; Stability; Subspace constraints; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-0164-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.155369
  • Filename
    155369