• DocumentCode
    1909313
  • Title

    Lambda learning rule for feedforward neural networks

  • Author

    Zurada, Jacek M.

  • Author_Institution
    Dept. of Electr. Eng., Louisville Univ., KY, USA
  • fYear
    1993
  • fDate
    1993
  • Firstpage
    1808
  • Abstract
    Feedforward layered networks of continuous perceptrons are traditionally trained using the delta and generalized delta training rules. These learning concepts are formalized in the error backpropagation training (EBPT) concept. Although the EBPT algorithm is widely used, the lambda learning rule often offers a considerable improvement in learning. Both the rule and the complete generalized lambda learning algorithm for layered networks are outlined. Emphasis is placed on visualization of learning. Comparisons between the two learning approaches are drawn
  • Keywords
    backpropagation; feedforward neural nets; continuous perceptrons; error backpropagation training; feedforward neural networks; lambda learning rule; layered networks; learning concepts; Acceleration; Feedforward neural networks; Neural networks; Neurons; Visualization; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993., IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7803-0999-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1993.298831
  • Filename
    298831