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Applied Intelligence

, Volume 20, Issue 1, pp 37–45 | Cite as

MIGA, A Software Tool for Nonlinear System Modelling with Modular Neural Networks

  • Bernardo Morcego
  • Josep M. Fuertes
  • Gabriela Cembrano
Article

Abstract

This paper presents a software tool suitable for dynamic system modelling. The models generated by this tool are modular neural networks, see [1]. Each module behaves like a functional block and is connected to the other modules like in classical block diagrams. This tool allows the inclusion of a priori knowledge and, furthermore, to extract physical information from the models, once the system has learned. The modelling tool is capable of automatic model generation, parameter estimation and model validation.

dynamic system modelling modular neural networks software tools knowledge acquisition 

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References

  1. 1.
    A.J. Sharkey (Ed.), Combining Artificial Neural Nets. Ensemble and Modular Multi-Net Systems, Springer-Verlag, 1999.Google Scholar
  2. 2.
    S.A. Billings, “Identification of nonlinear systems-a survey,” IEEE Proceedings vol. 127, no. 6, pp. 272–285, 1980.Google Scholar
  3. 3.
    R. Haber and H. Unbenhauen, “Structure identification of non linear dynamic systems-A survey on input/output approaches,” Automatica vol. 26, no. 4, pp. 651–677, 1990.Google Scholar
  4. 4.
    K.J. Hunt, D. Sbarbaro, R. Zbikowski, and P.J. Gawthrop, “Neural networks for control systems-A survey,” Automatica, vol. 28, no. 26, 1993.Google Scholar
  5. 5.
    Y. Bennani and P. Gallinari, “Task decomposition through a modular connectionist architecture: A talker identification system,” in Artificial Neural Networks, edited by I. Aleksander and J. Taylor, vol. 2, Elsevier Sience, 1992.Google Scholar
  6. 6.
    S.H. Chen and Y.F. Liao, “Modular recurrent neural networks for mandarin syllable recognition,” IEEE Transactions on Neural Networks, vol. 9, no. 6, 1998.Google Scholar
  7. 7.
    R.A. Jacobs and M.I. Jordan, “Learning piecewise control strategies in a modular neural network architecture,” IEEE Transactions on System, Man and Cybernetics, vol. 23, no. 2, 1993.Google Scholar
  8. 8.
    B.L.M. Happel and J.M.J. Murre, “The design and evolution of modular neural network architectures,” Neural Networks, vol. 7, pp. 985–1004, 1994.Google Scholar
  9. 9.
    B. Morcego, J.M. Fuertes, and G. Cembrano, “Neural modules: Networks with constrained architectures for nonlinear function identification,” in Proceedings of the International Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing, 1996.Google Scholar
  10. 10.
    B. Morcego, J.M. Fuertes, J. Codina, and G. Cembrano, “Modular neural network framework for nonlinear dynamic systems modeling,” TEMPUS Workshop MODIFY'97, 1997.Google Scholar
  11. 11.
    L.J. Fogel, A.J. Owens, and M.J. Walsh, Artificial Intelligence through Simulated Evolution, Wiley, 1966.Google Scholar
  12. 12.
    P.J. Angeline, G.M. Saunders, and J.B. Pollack, “An evolutionary algorithm that constructs recurrent neural networks,” IEEE Transactions on Neural Networks, vol. 5, no. 1. 1996.Google Scholar
  13. 13.
    R.A. Jacobs and M.I. Jordan, “Hierarchical mixtures of experts and the EM algorithm,” Neural Networks, vol. 6, 1994.Google Scholar
  14. 14.
    T. Catfolis, “Mapping a complex temporal problem into a combination of static and dynamic networks,” SIGART Bulletin, vol. 5, no. 3, 1994.Google Scholar
  15. 15.
    E.A.Wan and F. Beaufays, “Diagrammatic derivation of gradient algorithms for neural networks,” Neural Computation, no. 8, 1995.Google Scholar
  16. 16.
    L. Bottou and P. Gallinari, “A framework for the cooperation of learning algorithms,” Advances in Neural Processing Systems edited by R. Lippmann, J. Moody, and D.Touretzky (eds.), vol. 3, Morgan Kaufman, 1991.Google Scholar
  17. 17.
    B. Morcego, Study of Modular Neural Networks for Nonlinear Dynamic Systems Modeling. Ph.D. thesis (in Spanish), Universitat Politècnica de Catalunya, 2000.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Bernardo Morcego
    • 1
  • Josep M. Fuertes
    • 2
  • Gabriela Cembrano
    • 3
  1. 1.Automatic Control and Computer Engineering DepartmentUniversitat Politècnica de CatalunyaTerrassaSpain
  2. 2.Automatic Control and Computer Engineering DepartmentUniversitat Politècnica de CatalunyaBarcelonaSpain
  3. 3.Institut de Robòtica i Informàtica Industrial Universitat Politècnica de CatalunyaConsejo Superior de Investigaciones CientíficasBarcelonaSpain

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