Lempel-Ziv Complexity and the Individual-Sequence Approach to Information Theory

  1. M. Feder, N. Merhav, and M. Gutman, ``Universal prediction of individual sequences,'' IEEE Trans. Inform. Theory, vol. 38, no. 4, pp. 1258-1270, July 1992 (received the 1993 paper award of the Information Theory Society).
  2. N. Merhav and M. Feder, ``Universal schemes for sequential decision from individual data sequences,'' IEEE Trans. Inform. Theory vol. 39, no. 4, pp. 1280-1291, July 1993.
  3. J. Ziv and N. Merhav, ``A measure of relative entropy between individual sequences with application to universal classification,'' IEEE Trans. Inform. Theory, vol. 39, no. 4, pp. 1270-1279, July 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 and M. Feder, ``On the cost of universality of block codes for individual sequences,'' Proc. 1994 IEEE Int. Symp. on Information Theory (ISIT `94), p. 263, Trondheim, Norway, June 1994.
  6. N. Merhav and M. Feder, ``Universal prediction,'' (invited paper) IEEE Trans. Inform. Theory, vol. 44, no. 6, pp. 2124-2147, October 1998. (Commemorative issue for fifty years of Information Theory.) Also, in Information Theory: 50 Years of Discovery, pp. 80-103, Eds. S. Verdu and S. McLaughlin, IEEE Press, 1999.
  7. A. Baruch and N. Merhav, ``Universal filtering and prediction of individual sequences corrupted by noise using the Lempel-Ziv algorithm,'' Proc. 2000 IEEE Int. Symp. on Information Theory (ISIT 2000), p. 99, Sorrento, Italy, June 2000.
  8. T. Weissman and N. Merhav, ``Universal prediction of individual binary sequences in the presence of arbitrarily varying, memoryless, additive noise,'' Proc. 2000 IEEE Int. Symp. on Information Theory (ISIT 2000), p. 97, Sorrento, Italy, June 2000.
  9. N. Merhav, ``Universal detection of messages via finite-state channels,'' IEEE Trans. Inform. Theory, vol. 46, no. 6, pp. 2242-2246, September 2000.
  10. T. Weissman, N. Merhav, and A. Somekh-Baruch, ``Twofold universal prediction schemes for achieving the finite state predictability of a noisy individual binary sequence,'' IEEE Trans. Inform. Theory, vol 47, no. 5, pp. 1849-1866, July 2001.
  11. T. Weissman and N. Merhav, ``Universal prediction of binary individual sequences in the presence of noise,'' IEEE Trans. Inform. Theory, vol. 47, no. 6, pp. 2151-2173, September 2001.
  12. T. Weissman and N. Merhav, ``On limited-delay lossy coding and filtering of individual sequences,'' IEEE Trans. Inform. Theory, vol. 48, no. 3, pp. 721-733, March 2002.
  13. N. Merhav, E. Ordentlich, G. Seroussi, and M. J. Weinberger, ``On sequential strategies for loss functions with memory,'' IEEE Trans. Inform. Theory, vol. 48, no. 7, pp. 1947-1958, July 2002.
  14. E. Ordentlich, T. Weissman, M. J. Weinberger, A. Somekh-Baruch, and N. Merhav, ``Discrete universal filtering through incremental parsing,'' Proc. DCC 2004, Snowbird, Utah, March 2004.
  15. N. Merhav and J. Ziv, ``On the Wyner-Ziv problem for individual sequences,'' IEEE Trans. Inform. Theory, vol. 52, no. 3, pp. 867-873, March 2006.
  16. J. Ziv and N. Merhav, ``On context-tree prediction of individual sequences,'' IEEE Trans. Inform. Theory, vol. 53, no. 5, pp. 1860-1866, May 2007.
  17. T. Weissman, E. Ordentlich, M. J. Weinberger, A. Somekh-Baruch, and N. Merhav,'' ``Universal filtering via prediction,'' IEEE Trans. Inform. Theory, vol. 53, no. 4, pp. 1253-1264, April 2007.
  18. N. Merhav and E. Sabbag, ``Optimal watermark embedding and detection strategies under limited detection resources,'' IEEE Trans. Inform. Theory, vol. 54, no. 1, pp. 255-274, January 2008.
  19. A. Reani and N. Merhav, ``Efficient on-line schemes for encoding individual sequences with side information at the decoder,'' Proc. ISIT 2009, Seoul, Korea, June-July 2009. Full version: IEEE Trans. Inform. Theory, vol. 57, no. 10, pp. 6860-6876, October 2011.
  20. A. Martin, N. Merhav, G. Seroussi, and M. J. Weinberger, ``Twice-universal simulation of Markov sources and individual sequences,'' Proc. ISIT 2007, pp. 2876-2880, Nice, France, June 2007. Full version, appears in IEEE Trans. on Inform. Theory vol. 56, no. 9, pp. 4245-4255, Sept. 2010, and can be found here.
  21. N. Merhav, ``Perfectly secure encryption of individual sequences,'' IEEE Trans. Inform. Theory, vol. 59, no. 3, pp. 1302-1310, March 2013.
  22. N. Merhav, ``Universal decoding for arbitrary channels relative to a given class of decoding metrics,'' IEEE Trans. Inform. Theory, vol. 59, no. 9, pp. 5566-5576, September 2013.
  23. N. Merhav, ``On the data processing theorem in the semi-deterministic setting,'' IEEE Trans. Inform. Theory, vol. 60, no. 10, pp. 6032-6040, October 2014.
  24. N. Merhav, ``Sequence complexity and work extraction,'' Journal of Statistical Mechanics: Theory and Experiment, P06037, June 2015. doi:10.1088/1742-5468/2015/06/P06037
  25. 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.
  26. N. Merhav, ``Universal decoding using a noisy codebook,'' IEEE Trans. Inform. Theory, vol. 64, part 1, no. 4, pp. 2231-2239, April 2018.