Training of a feedforward multiple-valued neural network by error backpropagation with a multilevel threshold function

  • Authors:

  • V. K. Asari

  • Affiliations:

  • Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA

  • Venue:
  • IEEE Transactions on Neural Networks
  • Year:
  • 2001

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Abstract

A technique for the training of multiple-valued neural networks based on a backpropagation learning algorithm employing a multilevel threshold function is proposed. The optimum threshold width of the multilevel function and the range of the learning parameter to be chosen for convergence are derived. Trials performed on a benchmark problem demonstrate the convergence of the network within the specified range of parameters