The Transactions of the Korean Institute of Electrical Engineers D (대한전기학회논문지:시스템및제어부문D)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지

Feature Extraction of Letter Using Pattern Classifier Neural Network

패턴분류 신경회로망을 이용한 문자의 특징 추출

  • 류영재 (목포대 제어시스템공학과)
  • Published : 2003.02.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper describes a new pattern classifier neural network to extract the feature from a letter. The proposed pattern classifier is based on relative distance, which is measure between an input datum and the center of cluster group. So, the proposed classifier neural network is called relative neural network(RNN). According to definitions of the distance and the learning rule, the structure of RNN is designed and the pseudo code of the algorithm is described. In feature extraction of letter, RNN, in spite of deletion of learning rate, resulted in the identical performance with those of winner-take-all(WTA), and self-organizing-map(SOM) neural network. Thus, it is shown that RNN is suitable to extract the feature of a letter.

Keywords

References

  1. R. Desimone, 'Neural Networks for Vision and Image Processing', G. A. Carpenter and S. Grossber, Eds., Cambridge, MA: MIT Press, 1992
  2. Young-Jae Ryoo, Young-Cheol Lim, Kwang-Heon Kim, 'Classification of Materials Using Temperature Response Curve Fitting and Fuzzy Neural Network', Sensors and Actuators-A, Vol. 94, Issues No. 1-2, pp. 11-18, 2001 https://doi.org/10.1016/S0924-4247(01)00681-1
  3. Laurene Fausett, 'Fundamentals of Neural Networks Architectures, Algorithms, and Applications', Prentice Hall, 1994
  4. James A. Freeman and David M. Skapura, 'Neural Networks Algorithms, Applications, and Programming Techniques', Addison Wesley, 1992
  5. J. P. F. Sum, C. -S. Leung, K. S. Tam, G. H. Young, W. K. Kan, and L. Chan, 'Analysis for a Class of Winner-Take-All Model', IEEE Trans. on Neural Networks, Vol.10, No.1, pp. 64-71, 1999 https://doi.org/10.1109/72.737494
  6. S. Y. Kung, 'Digital neural networks', Prentice Hall, 1993
  7. T. Kohonen, 'Self-Organizing Maps', Springer-Verlag, 1995
  8. Helge Ritter, Thomas Martinetz, Klaus Schulten, 'Neural Computation and Self-Organizing Maps' Addison Wesley, 1992
  9. Neural Computation and Self-Organizing Maps Helge Ritter;Thomas Martinetz;Klaus Schulten