Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
권호 표지

On Designing Optimal Structure of Modular Wavelet Neural Network with Time-Frequency Analysis

시간-주파수 분석을 이용한 모듈라 웨이블렛 신경망의 최적 구조 설계

  • 서재용 (중앙대학교 전자공학과) ;
  • 김용택 (중앙대학교 전자공학과) ;
  • 조현찬 (한국기술교육대학교 전자공학과) ;
  • 전홍태 (한국기술교육대학교 전자공학과)
  • Published : 2001.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose the new algorithm which can design on the optimal structure of modular system. This system is composed to the wavelet neural network in order to simplify the structure of modular system and use the time-frequency analysis. We will determine the number of module and node of each sub-system using the proposed algorithm. This algorithm provides the methodology, which we will design optimal structure of modular wavelet neural network through analyzing the character of system. We apply the proposed new structure and algorithm to approximation problem and evaluate the effectiveness of the proposed system and algorithm.

본 논문에서는 새로운 구조의 모듈라 시스템의 최적구조 설계 알고리즘을 제안하였다. 모듈라 시스템은 구조의 단순화와 시간 주파수 분석법을 이용하기 위해 웨이블렛 신경망으로 구성하였다. 제안한 최적구조 설계 알고리즘을 이용하여 근사화 대상함수의 시간-주파수 특성을 분석하여 모듈의 개수와 부-시스템의 노드의 개수를 결정할 수 있다. 제안한 최적 구조 설계 알고리즘은 시스템의 특성을 분석하여 모듈라 웨이블렛 신경망의 최적구조를 설계할 수 있는 방법론을 제공할 수 있다. 제안한 새로운 구조와 최적 구조 설계 알고리즘을 근사화 문제에 적용하여 우수성을 검증하였다.

Keywords

References

  1. Simon Haykin, Neural Networks - A Comprehensive Foundation, Macmillian College Publishing Company Inc., 1994
  2. Y. C. Pati and P. S. Krishnaprasad, 'Analysis and synthesis of foodforward neural network using discretc affine wavelet transformations', IEEE Trans. on Neural Network, vol. 4, pp. 73-85, Jan. 1993 https://doi.org/10.1109/72.182697
  3. Ingrid Daubechies, 'The Wavelet Transform, Time-Frequency Localization and Signal Analysis,' IEEE Trans. on Information Theory, Vol. 36, No. 5, pp. 961-1005, 1990 https://doi.org/10.1109/18.57199
  4. Tomas Hrycej, Modular Learning in Neural Network, John Wiley & Sons Inc., 1992
  5. Gasser Auda and Mohamed Kamel, 'Modular Neural Network Classifiers: A Comparative Study,' Journal of Intelligent and Robotic Systems, Vol. 21, pp, 117-129, 1998 https://doi.org/10.1023/A:1007925203918
  6. G. Auda and M. Kamel, 'CMNN: Cooperative Modular Neural Networks for pattern recognition, 'Pattern Recognition Letters, V.18 pp. 11-13, 1997 https://doi.org/10.1016/S0167-8655(97)00108-6
  7. Eric Ronco, Henrik Gollee and Peter J. Gawthrop, 'Modular Neural Network and Self Decomposition,' Centre for Systems and Control, Technical Report CSC-96012, 1996
  8. Ke Chen, Liping Yang, Xiang Yu and Huisheng Chi, 'A self-generating modular neural network architecture for supervised learning,' Neurocomputing, Vol. 16, pp. 33-48, 1997 https://doi.org/10.1016/S0925-2312(96)00057-4
  9. R. A. Jacobs, M. I. Jordan, S. J. Nowlan, and G. E. Hinton, 'Adaptive Mixtures of Local Experts,' Neural Computation, Vol. 6., pp.181-214, 1994
  10. Michael I. Jordan and Robert A. Jacobs, 'Hierarchical Mixtures of Experts and the EM Algorithm,' Neural Computation, Vol. 6, No. 1, pp. 181-214, 1994
  11. Jacobs R. A. and Jordan M. I., 'Learning Piecewise Control Strategies in a Modular Neural Network Architecture,', IEEE Trans. Sys. Man and Cybernetics, Vol. 23, No. 2, pp. 337-345, 1993 https://doi.org/10.1109/21.229447
  12. M. N. Dailcy and G. W. Cottrell, 'Organization of face and object recognition in modular neural network models,' Neural Networks, Vol. 12, pp. 1053-1073, 1999 https://doi.org/10.1016/S0893-6080(99)00050-7
  13. Ath. Keagias and Vas. Petridis, 'Predictive Modular Neural Networks for Time Series Classification,' Neural Networks, Vol. 10, No. 1, pp. 31-49, 1997 https://doi.org/10.1016/S0893-6080(96)00040-8
  14. Wassim S. Chaer, Robert H. Bishop and Joydeep Ghish, 'A Mixture-of-Experts Framework for Adaptive Kalman Filtering,' IEEE Trans. on Systems, Man, and Cybernetics-Part B: Cybernetics, Vol. 27, No. 3, pp. 452-464, 1997 https://doi.org/10.1109/3477.584952
  15. Andreas S. Weigend, Morgan Mangcas, and Ashok N. Srivastava, 'Nonlinear Gated Experts for Time Series: Discovering Regimes and Avoiding Overfitting,' International Journal of Neural Systems, Vol. 6., pp.373-399, 1995 https://doi.org/10.1142/S0129065795000251
  16. Masumi Ishikawa, 'Learning of modular structured networks,' Artificial Intelligence, Vol. 75, pp. 51-62, 1995 https://doi.org/10.1016/0004-3702(94)00061-5
  17. Bao-Liang Lu and Masami Ito, 'Task Decomposition and Module Combination Based on Class Relations : A Modular Neural Network for Pattern Classification,' IEEE Trans. on Neural Networks, Vol. 10, No. 5, pp. 1244-1256, 1999 https://doi.org/10.1109/72.788664
  18. Viswanath Ramamuri and Joydeep Ghosh, 'Structurally Adaptive Modular Networks for Nonstationary Environments,' IEEE Trans. on Neural Networks, Vol. 10, No. 1,pp.152-160, 1999 https://doi.org/10.1109/72.737501