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The Capacity of a Possibilistic Channel

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2143))

Abstract

We put forward a model for transmission channels and channel coding which is possibilistic rather than probabilistic. We define a notion of possibilistic capacity, which is connected to a combinatorial notion called graph capacity. In the probabilistic case graph capacity is a relevant quantity only when the allowed decoding error probability is strictly equal to zero, while in the possibilistic case it is a relevant quantity for whatever value of the allowed decoding error possibility; as the allowed error possibility becomes larger the possibilistic capacity stepwise increases (one can reliably transmit data at a higher rate). We discuss an application, in which possibilities are used to cope with uncertainty as caused by a “vague” linguistic description of channel noise.

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References

  1. Borelli, M., Sgarro, A.: A Possibilistic Distance for Sequences of Equal and Unequal Length. In Finite VS Infinite, ed. by C. Călude and Gh. Păun, Discrete Mathematics and Theoretical Computer Science (Springer, 2000) 27–38

    Google Scholar 

  2. Bouchon-Meunier, B., Coletti, G., Marsala, C.: Possibilistic Conditional Events. IPMU 2000, Madrid, July 3–7 2000, Proceedings, 1561–1566

    Google Scholar 

  3. Cover, Th.M., Thomas, J.A.: Elements of Information Theory (Wiley, 1991)

    Google Scholar 

  4. Csiszár, I., Körner, J.: Information Theory (Academic Press, 1981)

    Google Scholar 

  5. DeCooman, G.: Possibility Theory. International Journal of General Systems25.4 (1997) 291–371

    Article  Google Scholar 

  6. Dubois, D., Nguyen, H.T., Prade, H.: Possibility Theory, Probability and Fuzzy Sets: Misunderstandings, Bridges and Gaps. In Fundamentals of Fuzzy Sets, ed. by D. Dubois and H. Prade (Kluwer Academic Publishers, 2000)

    Google Scholar 

  7. Dubois, D., Ostasiewicz, W., Prade, H.: Fuzzy Sets: History and Basic Notions. In Fundamentals of Fuzzy Sets, ed. by D. Dubois and H. Prade (Kluwer Academic Publishers, 2000)

    Google Scholar 

  8. Dubois, D., Prade, H.: Fuzzy Sets in Approximate Reasoning: Inference with Possibility Distribution. Fuzzy Sets and Systems 40 (1991) 143–202

    Article  MATH  MathSciNet  Google Scholar 

  9. Fabris, F., Sgarro, A.: Possibilistic Data Transmission and Fuzzy Integral Decoding, IPMU 2000, Madrid, July 3–7 2000, Proceedings, 1153–1158

    Google Scholar 

  10. Hisdal, E.: Conditional Possibilities, Independence and Non-Interaction. Fuzzy Sets and Systems 1 (1978) 283–297

    Article  MATH  Google Scholar 

  11. Klir, G.J., Folger, T.A.: Fuzzy Sets, Uncertainty and Information (Prentice-Hall, 1988)

    Google Scholar 

  12. Klir, G.J.: Measures of Uncertainty and Information. In Fundamentals of Fuzzy Sets, ed. by D. Dubois and H. Prade (Kluwer Academic Publishers, 2000)

    Google Scholar 

  13. Körner, J., Orlitsky, A.: Zero-error Information Theory. IEEE Transactions on Information Theory 44.6 (1998) 2207–2229

    Article  Google Scholar 

  14. Shannon, C.E.: A Mathematical Theory of Communication. Bell System Technical Journal 27.3&4 (1948) 379–423, 623-656

    MathSciNet  Google Scholar 

  15. Shannon, C.E.: The Zero-Error Capacity of a Noisy Channel, IRE Trans. Inform. Theory IT-2 (1956) 8–19

    Article  MathSciNet  Google Scholar 

  16. Sgarro, A.: Possibilistic Information Theory: a Coding Theoretic Approach, 2001, preliminary version at: http://www.dsm.univ.trieste.it/sgarro/possinfo.ps

  17. Zadeh, L.: Fuzzy Sets as a Basis for a Theory of Possibility Fuzzy Sets and Systems 1 (1978) 3–28

    MATH  MathSciNet  Google Scholar 

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© 2001 Springer-Verlag Berlin Heidelberg

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Sgarro, A. (2001). The Capacity of a Possibilistic Channel. In: Benferhat, S., Besnard, P. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2001. Lecture Notes in Computer Science(), vol 2143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44652-4_35

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  • DOI: https://doi.org/10.1007/3-540-44652-4_35

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42464-2

  • Online ISBN: 978-3-540-44652-1

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