Asymptotics of noisy constrained channel capacity

IEEE International Symposium on Information Theory - Proceedings

Volumn , Issue , 2007, Pages 991-995

  Han, Guangyue ^a   Marcus, Brian ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY SYMMETRIC CHANNEL; INTERNATIONAL SYMPOSIUM;

BOOLEAN FUNCTIONS; CHANNEL CAPACITY; CYBERNETICS; HIDDEN MARKOV MODELS; INFORMATION THEORY; SIGNAL THEORY; TECHNICAL PRESENTATIONS;

MARKOV PROCESSES;

EID: 51649126757     PISSN: 21578101     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIT.2007.4557353     Document Type: Conference Paper

References (24)

1. D. Arnold and H. Loeliger. The information rate of binary-input channels with memory. Proc. 2001 IEEE Int. Conf. on Communications, (Helsinki, Finland), pp. 2692-2695, June 11-14 2001.
2. S. Arimoto. An algorithm for computing the capacity of arbitrary memoryless channels. IEEE Trans. on Inform. Theory, vol. IT-18, no. 1, pp. 14-20, 1972.
3. J. J. Birch. Approximations for the entropy for functions of Markov chains. Ann. Math. Statist., 33:930-938, 1962.
4. D. Blackwell. The entropy of functions of finite-state Markov chains. Trans. First Prague Conf. Information Thoery, Statistical Decision Functions, Random Processes, pages 13-20, 1957.
5. R. E. Blahut. Computation of channel capacity and rate distortion functions. IEEE Trans. on Inform. Theory, vol. IT-18, no. 4, pp. 460-473, 1972.
6. L. Breiman. On achieving channel capacity in finite-memory channels. Illinois J. Math. 4 1960 246-252.
7. J. Chen and P. Siegel. Markov Processes Asymptotically Achieve the Capacity of Finite-State Intersymbol Interference Channels. Proceedings of the 2004 IEEE International Symposium on Information Theory, page 346, June 27-July 2, Chicago, U.S.A., 2004.
8. S. Egner, V. Balakirsky, L. Tolhuizen, S. Baggen and H. Hollmann. On the entropy rate of a hidden Markov model. Proceedings of the 2004 IEEE International Symposium on Information Theory, page 12, June 27-July 2, Chicago, U.S.A., 2004.
9. G. Han and B. Marcus. Analyticity of entropy rate of hidden Markov chains. IEEE Transactions on Information Theory, Volume 52, Issue 12, December, 2006, pages: 5251-5266.
10. G. Han and B. Marcus. Derivatives of Entropy Rate in Special Familes of Hidden Markov Chains. To appear in IEEE Transactions on Information Theory.
11. R. Gharavi and V. Anantharam. An upperbound for the largest Lyapunov exponent of a Markovian product of nonnegative matrices. Theoretical Computer Science, Vol. 332, Nos. 1-3, pp. 543-557, February 2005.
12. T. Holliday, A. Goldsmith, and P. Glynn. Capacity of Finite State Channels Based on Lyapunov Exponents of Random Matrices. IEEE Transactions on Information Theory, Volume 52, Issue 8, Aug. 2006, Page(s):3509 - 3532
13. P. Jacquet, G. Seroussi and W. Szpankowski. On the Entropy of a Hidden Markov Process. Data Compression Conference, 362-371, Snowbird, 2004.
14. P. Jacquet, G. Seroussi and W. Szpankowski. Noisy Constrained Capacity. Preprint. December, 2006.
15. D. Lind and B. Marcus. An Introduction to Symbolic Dynamics and Coding. Cambridge University Press, 1995.
16. B. Marcus, K. Petersen and S. Williams. Transmission rates and factors of Markov chains. Contemporary Mathematics, 26:279-294, 1984.
17. E. Ordentlich and T. Weissman. On the optimality of symbol by symbol filtering and denoising. Information Theory, IEEE Transactions, Volume 52, Issue 1, Jan. 2006 Page(s):19 - 40.
18. E. Ordentlich and T. Weissman. New bounds on the entropy rate of hidden Markov process. Information Theory Workshop, 2004. IEEE 24-29 Oct. 2004 Page(s):117 - 122.
19. W. Parry. Intrinsic Markov chains. Trans. Amer. Math. Soc. 112 (1964), 55-66.
20. P. Vontobel, A. Kavcic, D. Arnold and Hans-Andrea Loeliger. Capacity of Finite-State Machine Channels. Submitted to IEEE Transactions on Information Theory, November 29, 2004.
21. H. Pfister, J. Soriaga and P. Siegel. The achievable information rates of finite-state ISI channels. Proc. IEEE GLOBECOM, (San Antonio, TX), pp. 2992-2996, Nov. 2001.
22. V. Sharma and S. Singh. Entropy and channel capacity in the regenerative setup with applications to Markov channels. Proc. IEEE Intern. Symp. on Inform. Theory, (Washington, D.C.), p. 283, June 24-29 2001.
23. O. Zuk, I. Kanter and E. Domany. The entropy of a binary hidden Markov process. J. Stat. Phys., 121(3-4): 343-360 (2005)
24. O. Zuk, E. Domany, I. Kanter, and M. Aizenman. Taylor series expansions for the entropy rate of hidden Markov Processes. ICC 2006, Istanbul.