• DocumentCode
    274708
  • Title

    Object oriented neural networks

  • Author

    Emam, K. El ; Khalafalla, F.B. ; Hoptroff, R.G. ; Hall, T.J.

  • Author_Institution
    King´´s Coll., London, UK
  • fYear
    1991
  • fDate
    25-28 Mar 1991
  • Firstpage
    1007
  • Lastpage
    1010
  • Abstract
    Artificial neural networks offer feasible solutions to highly complex problems, such as those encountered in many control problems. Their potency lies primarily in providing a suitable framework for the development of knowledge representation systems. The paper outlines the compatibility and advantages of object-oriented technology for software simulation and application of neural networks. For this, a number of computational models are discussed, particularly in relation to concurrency and distributed processing, real-time performance issues, fault tolerance and accuracy. A brief description of the implementation of the C++ programming language is presented
  • Keywords
    learning systems; neural nets; object-oriented programming; parallel processing; software reusability; C++; accuracy; concurrency; distributed processing; fault tolerance; knowledge representation systems; object-oriented neural nets; real-time performance issues; software simulation;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Control 1991. Control '91., International Conference on
  • Conference_Location
    Edinburgh
  • Print_ISBN
    0-85296-509-5
  • Type

    conf

  • Filename
    98588