Skip to main content
SpringerLink
Log in
Book cover

International Work-Conference on Artificial Neural Networks

IWANN 1997: Biological and Artificial Computation: From Neuroscience to Technology pp 273–283Cite as

An introduction to Fuzzy State Automata

  • Formal Tools and Computational Models of Neurons and Neural Net Architectures
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1240))

Abstract

This paper introduces Fuzzy State Automata for control applications. They are derived from the integration of traditional finite state automata and neuro-fuzzy systems, where a finite state automaton tracks the state of the plant under control and modifies the characteristic of the neuro-fuzzy system accordingly. The main difference with respect to existing systems is that the states of the automata are identified by fuzzy, instead of crisp variables, therefore state transitions and the corresponding controller characteristic are smoother and easier to train or tune.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. Haykin, “Neural Networks: A Comprehensive Foundation”, Mc Millan College Publishing Company, New York, 1994.

    Google Scholar 

  2. L. Wang, “Adaptive Fuzzy Systems and Control”, Prentice Hall, Englewood Cliffs, New Jersey, 1994.

    Google Scholar 

  3. D.A. White and D.A. Sofge, “Handbook of Intelligent Control”, Van Nostrand Reinhold, 1992.

    Google Scholar 

  4. L.M. Reyneri, “Weighted Radial Basis Functions for Improved Pattern Recognition and Signal Processing”, submitted to Neural Letters.

    Google Scholar 

  5. L.M. Reyneri, M. Chiaberge, L. Zocca, “CINTIA: A Neuro-Fuzzy Real Time Controller for Low Power Embedded Systems”, IEEE MICRO, special issue on Hardware for Artificial Neural Networks, June 1995, pp. 40–47.

    Google Scholar 

  6. F. Berardi, M. Chiaberge, E. Miranda, L.M. Reyneri, “A Walking Hexapod Controlled by a Neuro-Fuzzy System”, Proc. of MCPA'97, Pisa (I), February 1997 (to be published).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Elettronica, Politecnico di Torino, C.so Duca Abruzzi, 24, 10129, Torino, Italy

    L. M. Reyneri

Authors
  1. L. M. Reyneri
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

José Mira Roberto Moreno-Díaz Joan Cabestany

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Reyneri, L.M. (1997). An introduction to Fuzzy State Automata. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032485

Download citation

  • DOI: https://doi.org/10.1007/BFb0032485

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63047-0

  • Online ISBN: 978-3-540-69074-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation