Universal Hypothesis Testing and Universal Decoding

Universal Hypothesis Testing
  1. N. Merhav, M. Gutman, and J. Ziv, ``On the estimation of the order of a Markov chain and universal data compression,'' IEEE Trans. Inform. Theory vol. 35, no. 5, pp. 1014-1019, September 1989.
  2. N. Merhav, ``On the estimation of the model order in exponential families,'' IEEE Trans. Inform. Theory, vol. IT-35, no. 5, pp. 1109-1114, September 1989.
  3. J. Ziv and N. Merhav, ``Estimating the number of states of a finite-state source,'' IEEE Trans. Inform. Theory, vol. 38, no. 1, pp. 61-65, January 1992.
  4. O. Zeitouni, J. Ziv, and N. Merhav, ``When is the generalized likelihood ratio test optimal?'' IEEE Trans. Inform. Theory, vol. 38, no. 5, pp. 1597-1602, September 1992.
  5. 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.
  6. N. Merhav, ``Universal detection of messages via finite-state channels,'' IEEE Trans. Inform. Theory, vol. 46, no. 6, pp. 2242-2246, September 2000.
  7. M. Feder and N. Merhav, ``Universal composite hypothesis testing: A competitive minimax approach,'' (invited paper) IEEE Trans. Inform. Theory, special issue in memory of Aaron D. Wyner, vol. 48, no. 6, pp. 1504-1517, June 2002.
  8. E. Levitan and N. Merhav, ``A competitive Neyman-Pearson approach to universal hypothesis testing with applications,'' IEEE Trans. Inform. Theory, vol. 48, no. 8, pp. 2215-2229, August 2002.
  9. N. Merhav, ``An information-theoretic view of watermark embedding-detection and geometric attacks,'' presented at WaCha `05 , Barcelona, Spain, June 2005.
  10. 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.
  11. 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.
  12. N. Weinberger and N. Merhav, ``Channel detection in coded communication,'' IEEE Trans. Inform. Theory, vol. 63, no. 10, pp. 6364-6392, October 2017.
  13. B. Tondi, M. Barni, and N. Merhav, ``Detection games with a fully active attacker,'' in Proc. 7th IEEE Innternational Workshop on Information Forensics and Security (WIFS 2015), Rome, Italy, November 16-19, 2015.
  14. B. Tondi, N. Merhav and M. Barni, ``Detection games under fully active adversaries,'' Entropy, 2019, 21(1), 23; doi: 10.3390/e21010023, special issue on Probabilistic Methods in Information Theory, Hypothesis Testing, and Coding, published on December 29, 2018.
Universal Decoding
  1. N. Merhav, ``Universal decoding for memoryless Gaussian channels with a deterministic interference,'' IEEE Trans. Inform. Theory, vol. 39, no. 4, pp. 1261-1269, July 1993
  2. M. Feder and N. Merhav, ``Universal composite hypothesis testing: A competitive minimax approach,'' (invited paper) IEEE Trans. Inform. Theory, special issue in memory of Aaron D. Wyner, vol. 48, no. 6, pp. 1504-1517, June 2002.
  3. N. Merhav and M. Feder, ``Minimax universal decoding with an erasure option,'' IEEE Trans. Inform. Theory, vol. 53, no. 5, pp. 1664-1675, May 2007.
  4. Y. Akirav and N. Merhav, ``Competitive minimax universal decoding for several ensembles of random codes,'' IEEE Trans. Inform. Theory, vol. 55, no. 4, pp. 1450-1459, April 2009.
  5. 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.
  6. W. Huleihel and N. Merhav, ``Universal decoding for Gaussian intersymbol inteference channels,'' IEEE Trans. Inform. Theory, vol. 61, no. 4, pp. 1606-1618, April 2015.
  7. W. Huleihel, N. Weinberger and N. Merhav, ``Erasure/list random coding error exponents are not universally achievable,'' IEEE Trans. Inform. Theory, vol. 62, no. 10, pp. 5403-5421, October 2016.
  8. N. Merhav, ``Universal decoding for source-channel coding with side information,'' Communications in Information and Systems, vol. 16, no. 1, pp. 17-58, 2016.
  9. N. Merhav, ``Universal decoding using a noisy codebook,'' IEEE Trans. Inform. Theory, vol. 64, part 1, no. 4, pp. 2231-2239, April 2018.
  10. N. Merhav, ``Reliability of universal decoding based on vector-quantized codewords,'' IEEE Trans. Inform. Theory, vol. 63, no. 5, pp. 2696-2709, May 2017.
  11. R. Averbuch and N. Merhav, ``Exact random coding exponents and universal decoders for the asymmetric broadcast channel,'' IEEE Trans. Inform. Theory, vol. 64, no. 7, pp. 5070-5086, July 2018.
  12. R. Tamir (Averbuch) and N. Merhav, ``Universal decoding for the typical random code and for the expurgated code,'' accepted to IEEE Trans. Inform. Theory, December 2021.
  13. N. Merhav, ``Universal decoding for asynchronous Slepian-Wolf encoding,'' IEEE Trans. Inform. Theory, vol. 67, no. 5, pp. 2652-2662, May 2021.
  14. N. Weinberger and N. Merhav, ``The DNA-storage channel: capacity and error probability bounds,'' submitted for publication, August 2021.