• DocumentCode
    3109188
  • Title

    Cellular neural network design using a learning algorithm

  • Author

    Zou, Fan ; Schwarz, Stephan ; Nossek, Josef

  • Author_Institution
    Inst. for Network Theory & Circuit Design, Tech. Univ. of Munich, Germany
  • fYear
    1990
  • fDate
    16-19 Dec 1990
  • Firstpage
    73
  • Lastpage
    81
  • Abstract
    A learning algorithm for cellular neural networks (CNN) is proposed. The cloning templates can be obtained by using this algorithm, which is based on the relaxation method for solving sets of linear inequalities. The symmetry of templates can be forced through additional equality constraints. Simulation examples show that some useful templates with the smallest neighborhood N1(i , j) are generated by the application of the training rule
  • Keywords
    learning systems; neural nets; relaxation theory; cellular neural networks; cloning templates; learning algorithm; linear inequalities; relaxation method; Algorithm design and analysis; Cellular neural networks; Circuit synthesis; Cloning; Equations; Image processing; Integrated circuit interconnections; Neural networks; Noise generators; Relaxation methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1990. CNNA-90 Proceedings., 1990 IEEE International Workshop on
  • Conference_Location
    Budapest
  • Type

    conf

  • DOI
    10.1109/CNNA.1990.207509
  • Filename
    207509
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3109188