A Biological Fuzzy Multilayer Perceptron Algorithm

  • Kim, Kwang-Baek (Computer Engineering Department, University of Silla) ;
  • Seo, Chang-Jin (Computer Information Division, College of Sungdu) ;
  • Yang, Hwang-Kyu (Internet Engineering Division, University of Dongseo)
  • Published : 2003.09.01


A biologically inspired fuzzy multilayer perceptron is proposed in this paper. The proposed algorithm is established under consideration of biological neuronal structure as well as fuzzy logic operation. We applied this suggested learning algorithm to benchmark problem in neural network such as exclusive OR and 3-bit parity, and to digit image recognition problems. For the comparison between the existing and proposed neural networks, the convergence speed is measured. The result of our simulation indicates that the convergence speed of the proposed learning algorithm is much faster than that of conventional backpropagation algorithm. Furthermore, in the image recognition task, the recognition rate of our learning algorithm is higher than of conventional backpropagation algorithm.


Biological Neuron Structure;Antagonistic Interaction;Directionality of Synaptic Transmission;Inhibitory Neuron;Excitatory Neuron;Activated Neuron


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