• DocumentCode
    2361563
  • Title

    Representation of complex-valued neural networks: a real-valued approach

  • Author

    Yadav, A. ; Mishra, D. ; Ray, S. ; Yadav, R.N. ; Kalra, P.K.

  • Author_Institution
    Dept. of Electr. Eng., Indian Inst. of Technol., Kanpur, India
  • fYear
    2005
  • fDate
    4-7 Jan. 2005
  • Firstpage
    331
  • Lastpage
    335
  • Abstract
    A methodology for representing a complex-valued multilayer artificial neural network and its backpropagation learning algorithm in terms of real-valued neural network has been discussed. The performance of the proposed method has been tested on complex-valued XOR problem and power system load flow problems.
  • Keywords
    backpropagation; feedforward neural nets; load distribution; multilayer perceptrons; XOR problem; backpropagation learning algorithm; complex nonlinear bounded activation function; complex-valued multilayer artificial neural network; power system load flow problem; Artificial neural networks; Backpropagation; Circuits; Load flow; Multi-layer neural network; Neural networks; Neurons; Power systems; Remote sensing; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensing and Information Processing, 2005. Proceedings of 2005 International Conference on
  • Print_ISBN
    0-7803-8840-2
  • Type

    conf

  • DOI
    10.1109/ICISIP.2005.1529471
  • Filename
    1529471
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2361563