Lossless Source Coding

  1. N. Merhav, ``Universal coding with minimum probability of code word length overflow,'' IEEE Trans. Inform. Theory vol. 37, no. 3, pp. 556-563, May 1991.
  2. N. Merhav and D. L. Neuhoff, ``Variable-to-fixed length codes provide better large deviations performance than fixed-to-variable length codes,'' IEEE Trans. Inform. Theory, vol. 38, no. 1, pp. 135-140, January 1992.
  3. N. Merhav, ``On the minimum description length principle for sources with piecewise constant parameters,'' IEEE Trans. Inform. Theory, vol. 39, no. 6, pp. 1962-1967, November 1993.
  4. M. J. Weinberger, N. Merhav, and M. Feder, ``Optimal sequential probability assignment for individual sequences,'' IEEE Trans. Inform. Theory vol. 40, no. 2, pp. 384-396, March 1994.
  5. N. Merhav, ``Bounds on achievable convergence rates of parameter estimators via universal coding,'' IEEE Trans. Inform. Theory, vol. 40, no. 4, pp. 1210-1215, July 1994.
  6. N. Merhav and M. Feder, ``A strong version of the redundancy-capacity theorem of universal coding,'' IEEE Trans. Inform. Theory, vol. 41, no. 3, pp. 714-722, May 1995.
  7. M. Feder and N. Merhav, ``Universal coding for arbitrarily varying sources,'' Proc. 1995 IEEE Int. Symp. on Information Theory, (ISIT `95), p. 16, Whistler, British Columbia, Canada, September 1995.
  8. M. Feder and N. Merhav, ``Hierarchical universal coding,'' IEEE Trans. Inform. Theory, vol. 42, no. 5, pp. 1354-1364, September 1996.
  9. G. I. Shamir and N. Merhav, ``Low-complexity sequential lossless coding for piecewise stationary memoryless sources,'' IEEE Trans. Inform. Theory, vol. 45, no. 5, pp. 1498-1519, July 1999.
  10. N. Merhav, G. Seroussi, and M. J. Weinberger, ``Optimal prefix codes for sources with two-sided geometric distributions,'' IEEE Trans. Inform. Theory, vol. 46, no. 1, pp. 121-135, January 2000.
  11. N. Merhav, G. Seroussi, and M. J. Weinberger, ``Coding of sources with two-sided geometric distributions and unknown parameters,'' IEEE Trans. Inform. Theory, vol. 46, no. 1, pp. 229-236, January 2000.
  12. N. Merhav, ``Relations between redundancy patterns of the Shannon code and wave diffraction patterns of partially disordered media,'' IEEE Trans. Inform. Theory, vol. 58, no. 6, pp. 3402-3406, June 2012.
  13. N. Merhav, ``2SSubset-sum phase transitions and data compression,'' Journal of Statistical Mechanics: Theory and Experiment, P09017, September 2011, doi: 10.1088/1742-5468/2011/09/P01029
  14. N. Merhav and W. Szpankowsi, ``Average redundancy of the Shannon code for Markov sources,'' IEEE Trans. Inform. Theory, vol. 59, no. 11, pp. 7186-7193, November 2013.
  15. N. Merhav, ``Erasure/list exponents for Slepian-Wolf decoding,'' IEEE Trans. Inform. Theory, vol. 60, no. 8, pp. 4463-4471, August 2014.
  16. N. Merhav, ``Asymptotically optimal decision rules for joint detection and source coding,'' IEEE Trans. Inform. Theory, vol. 60, no. 11, pp. 6787-6795, November 2014.
  17. Y. Kaspi and N. Merhav, ``Zero-delay and causal secure source coding,'' IEEE Trans. Inform. Theory, vol. 61, no. 11, pp. 6238-6250, November 2015.
  18. N. Weinberger and N. Merhav, ``Large deviations analysis of variable-rate Slepian-Wolf coding,'' IEEE Trans. Inform. Theory, vol. 61, no. 4, pp. 2165-2190, April 2015.
  19. N. Merhav, ``Statistical physics of random binning,'' IEEE Trans. Inform. Theory, vol. 61, no. 5, pp. 2454-2464, May 2015.
  20. N. Merhav, ``On empirical cumulant generating functions of code lengths for individual sequences,'' IEEE Trans. Inform. Theory, vol. 63, no. 12, pp. 7729-7736, December 2017.
  21. N. Merhav and A. Cohen, ``Universal randomized guessing with application to asynchronous decentralized brute-force attacks,'' IEEE Trans. Inform. Theory, vol. 66, no. 1, pp. 114-129, January 2020.
  22. N. Merhav, ``Guessing individual sequences: generating randomized guesses using finite-state machines,'' IEEE Trans. Inform. Theory, Journal of Statistical Mechanics: Theory and Experiment, P09017, September 2011, doi: 10.1088/1742-5468/2011/09/P01029
  23. N. Merhav and W. Szpankowsi, ``Average redundancy of the Shannon code for Markov sources,'' IEEE Trans. Inform. Theory, vol. 59, no. 11, pp. 7186-7193, November 2013.
  24. N. Merhav, ``Erasure/list exponents for Slepian-Wolf decoding,'' IEEE Trans. Inform. Theory, vol. 60, no. 8, pp. 4463-4471, August 2014.
  25. N. Merhav, ``Asymptotically optimal decision rules for joint detection and source coding,'' IEEE Trans. Inform. Theory, vol. 60, no. 11, pp. 6787-6795, November 2014.
  26. Y. Kaspi and N. Merhav, ``Zero-delay and causal secure source coding,'' IEEE Trans. Inform. Theory, vol. 61, no. 11, pp. 6238-6250, November 2015.
  27. N. Weinberger and N. Merhav, ``Large deviations analysis of variable-rate Slepian-Wolf coding,'' IEEE Trans. Inform. Theory, vol. 61, no. 4, pp. 2165-2190, April 2015.
  28. N. Merhav, ``Statistical physics of random binning,'' IEEE Trans. Inform. Theory, vol. 61, no. 5, pp. 2454-2464, May 2015.
  29. N. Merhav, ``On empirical cumulant generating functions of code lengths for individual sequences,'' IEEE Trans. Inform. Theory, vol. 63, no. 12, pp. 7729-7736, December 2017.
  30. N. Merhav and A. Cohen, ``Universal randomized guessing with application to asynchronous decentralized brute-force attacks,'' IEEE Trans. Inform. Theory, vol. 66, no. 1, pp. 114-129, January 2020.
  31. N. Merhav, ``Guessing individual sequences: generating randomized guesses using finite-state machines,'' IEEE Trans. Inform. Theory, vol. 66, no. 5, pp. 2912--2920, May 2020.
  32. R. Tamir (Averbuch) and N. Merhav, ``Trade-offs between error exponents and excess-rate exponents of typical Slepian-Wolf codes, Entropy 23, 265. https://doi.org/10.3390/e23030265 February 2021.
  33. N. Merhav, ``Universal decoding for asynchronous Slepian-Wolf encoding,'' IEEE Trans. Inform. Theory, vol. 67, no. 5, pp. 2652-2662, May 2021.
  34. N. Merhav, ``On more general distributions of random binning for Slepian-Wolf encoding,'' IEEE Trans. Inform. Theory, vol. 68, no. 2, pp. 737-751, February 2022.
  35. N. Merhav, ``Universal Slepian-Wolf coding for individual sequences,'' submitted for publication, March 2024.