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Applications on Information Flow and Biomedical Treatment of FDES Based on Fuzzy Sequential Machines Theory

  • Hongyan Xing
  • Daowen Qiu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7389)

Abstract

In order to more effectively cope with the real world problems of vagueness, impreciseness, and subjectivity, fuzzy discrete event systems (FDES) were proposed and developed in recent ten years. In this paper, we study the applications of FDES to information flow inference and then, to biomedical control treatment planning and decision making based on fuzzy sequential machines (FSM) theory. Through modeling security system and biomedical decision problem with FDES as an FSM, we extend propositions and procedures to decide the equivalent states, display the ideas for checking the observation label based on event-state approach to decide whether hidden massage flow exists.

Keywords

fuzzy sequential machines fuzzy discrete event systems information flow supervisory control 

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References

  1. 1.
    Cassandras, C.G., Lafortune, S.: Introduction to Discrete Event Systems. Kluwer, Boston (1999)zbMATHGoogle Scholar
  2. 2.
    Lin, F., Ying, H.: Modeling and Control of Fuzzy Discrete Event Systems. IEEE Transactions on System, Man, Cybern., B 32(4), 408–415 (2002)CrossRefGoogle Scholar
  3. 3.
    Qiu, D.W.: Supervisory Control of Fuzzy Discrete Event Systems: A Formal Approach. IEEE Transactions on System, Man, Cybern., B 35(2), 72–88 (2005)CrossRefGoogle Scholar
  4. 4.
    Zi, X.C., Yao, L.H., Li, L.: A State-based Approach to Information Flow Analysis. J. of Computers 29(8), 1460–1467 (2006) (in Chinese)Google Scholar
  5. 5.
    Goguren, J.A., Messegurer, J.: Security Policies and Security Models. In: Proceedings of the IEEE Symposium on Security and Privacy, California, USA, pp. 75–85 (1984)Google Scholar
  6. 6.
    Zakintihinos, A., Lee, E.S.: A General Theory of Security Properties. In: Proceedings of the IEEE Symposium on Security and Privacy, California, USA, pp. 94–102 (1997)Google Scholar
  7. 7.
    Shayman, M.A., Kumar, R.: Supervisory Control of Nondeterministic Systems with Driven Events via Prioritized Synchronization and Trajectory Models. SIAM J. Control Optim. 33(2), 469–497 (1995)MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    Thomason, M.G., Marinos, P.N.: Deterministic Acceptors of Regular Fuzzy Languages. IEEE Transactions on System, Man and Cyber. 4(1), 228–230 (1974)MathSciNetzbMATHGoogle Scholar
  9. 9.
    Kumar, R., Heymann, M.: Masked Prioritized Synchronization for Interaction and Control of Discrete Event Systems. IEEE Transactions on Automatic Control 45(11), 1970–1982 (2000)MathSciNetzbMATHCrossRefGoogle Scholar
  10. 10.
    Looney, C.G.: Fuzzy Petri Nets for Rule-based Decision making. IEEE Trans. Syst., Man, Cybern. 18(1), 178–183 (1988)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hongyan Xing
    • 1
    • 3
  • Daowen Qiu
    • 1
    • 2
  1. 1.Department of Computer ScienceSun Yat-sen UniversityGuangzhouP.R. China
  2. 2.SQIG–Instituto de Telecomunicações, Departamento de Matemática, Instituto Superior TécnicoTULisbonLisbonPortugal
  3. 3.Faculty of Applied MathematicsGuangdong University of TechnologyGuangzhouP.R. China

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