Guessing subject to distortion

IEEE Transactions on Information Theory

Volumn 44, Issue 3, 1998, Pages 1041-1056

  Arikan, Erdal ^a,c   Merhav, Neri ^b,c  

^a BILKENT UNIVERSITY   (Turkey)

^b HEWLETT PACKARD LABORATORIES   (United States)

^c TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Fidelity criterion; Guessing; Rate distortion theory; Side information; Source coding; Source coding error exponent

Indexed keywords

ALGORITHMS; BLOCK CODES; ERRORS; FUNCTIONS; GAME THEORY; MATHEMATICAL MODELS; PROBABILITY; VECTORS;

FIDELITY CRITERION; GUESSING; RATE DISTORTION THEORY; SIDE INFORMATION; SOURCE CODING; SOURCE CODING ERROR EXPONENT;

INFORMATION THEORY;

EID: 0032072149     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/18.669158     Document Type: Article

References (20)

1. R. Ahlswede, "Extremal properties of rate-distortion functions," IEEE Trans. Inform. Theory, vol. 36, pp. 166-171, Jan. 1990.
2. E. Arikan, "An inequality on guessing and its application to sequential decoding," IEEE Trans. Inform. Theory, vol. 42, pp. 99-105, Jan. 1996.
3. T. Berger, Rate Distortion Theory: A Mathematical Basis for Data Compression. Englewood Cliffs, NJ: Prentice-Hall, 1971.
4. R. E. Blahut, Principles and Practice of Information Theory. Reading, MA: Addison-Wesley, 1987.
5. I. Csiszár, "Generalized cutoff rates and Rényi's information measures," IEEE Trans. Inform. Theory, vol. 41, pp. 26-34, Jan. 1995.
6. I. Csiszár and J. Körner, Information Theory: Coding Theorems for Discrete Memoryless Systems. New York: Academic, 1981.
7. A. Dembo and O. Zeitouni, Large Deviations Techinques and Applications. Jones and Bartlett, 1993.
8. W. H. R. Equitz and T. M. Cover, "Successive refinement of information," IEEE Trans. Inform. Theory, vol. 37, pp. 269-274, Mar. 1991.
9. R. G. Gallager, Information Theory and Reliable Communication. New York: Wiley, 1968.
10. P. A. Humblet, "Generalization of Hoffman coding to minimize the probability of buffer overflow," IEEE Trans. Inform. Theory, vol. IT-27, pp. 230-232, Mar. 1981.
11. F. Jelinek, "Buffer overflow in variable length coding of fixed rate sources," IEEE Trans. Inform. Theory, vol. IT-14, pp. 490-501, May 1968.
12. K. Marton, "Error exponent for source coding with a fidelity criterion," IEEE Trans. Inform. Theory, vol. IT-20, pp. 197-199, Jan. 1974.
13. N. Merhav, "Universal decoding for memoryless Gaussian channels with a deterministic interference," IEEE Trans. Inform. Theory, vol. 39, pp. 1261-1269, July 1993.
14. _, "On list size exponents in rate-distortion coding," submitted for publication, 1995.
15. _, "Universal coding with minimum probability of code word length overflow," IEEE Trans. Inform. Theory, vol. 37, pp. 556-563, May 1991.
16. A. Rényi, "On measures of entropy and information," in Proc. 4th Berkeley Symp. on Mathematical Statistics and Probability (Berkeley, CA, 1961), vol. 1, pp. 547-561.
17. R. T. Rockafellar, Convex Analysis. Princeton, NJ: Princeton Univ. Press, 1970.
18. M. J. Weinberger, J. Ziv, and A. Lempel, "On the optimal asymptotic performance of universal ordering and of discrimination of individual sequences," IEEE Trans. Inform. Theory, vol. 38, pp. 380-385, Mar. 1992.
19. A.D. Wyner, "On the probability of buffer overflow under an arbitrary bounded input-output distribution," SIAM J. Appl. Math., vol. 27, no. 4, pp. 544-570, Dec. 1974.
20. B. Yu and T. P. Speed, "A rate of convergence result for a D-semifaithful code," IEEE Trans. Inform. Theory, vol. 39, pp. 813-820, May 1993.