Signal Processing, Detection/Estimation Theory, and Parameter Modulation-Estimation

Signal Processing
  1. N. Merhav and C.-H. Lee, ``A minimax classification approach with application to robust speech recognition,'' IEEE Trans. Speech and Audio Processing, vol. SAP-1, no. 1, pp. 90-100, January 1993.
  2. N. Merhav and C.-H. Lee, ``On the asymptotic statistical behavior of empirical cepstral coefficients,'' IEEE Trans. Signal Processing, vol. SP-41, no. 5, pp. 1990-1993, May 1993.
Detection/Estimation Theory
  1. N. Merhav and J. Ziv, ``On universally efficient estimation of the first-order autoregressive parameter, and universal data compression,'' IEEE Trans. Inform. Theory vol. 36, no. 6, pp. 1245-1254, November 1990.
  2. Y. Ephraim and N. Merhav, ``Lower and upper bounds on the minimum mean square error in composite source signal estimation,'' IEEE Trans. Inform. Theory, vol. 38, no. 6, pp. 1709-1724, November 1992.
  3. 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.
  4. Y. Ephraim, N. Merhav, and H. L. Van Trees, ``Min-Norm interpretations and consistency of MUSIC, MODE and ML,'' IEEE Trans. Signal Processing, vol. SP-43, no. 12, pp. 2937-2942, December 1995.
  5. D. Hirshberg and N. Merhav, ``Robust methods for model order estimation,'' IEEE Trans. on Signal Processing, vol. SP-44, no. 3, pp. 620-628, March 1996.
  6. J. Stein, J. Ziv, and N. Merhav, ``Universal delay estimation for discrete channels,'' IEEE Trans. on Inform. Theory, vol. 42, Part II, no. 6, pp. 2085-2093, November 1996.
  7. Y. C. Eldar and N. Merhav, ``A competitive minimax approach to robust estimation in linear models,'' IEEE Trans. Signal Processing, vol. 52, no. 7, pp. 1931-1946, July 2004.
  8. I. Hen and N. Merhav, ``On the threshold effect in the estimation of chaotic sequences,'' IEEE Trans. Inform. Theory, vol. 50, no. 11, pp. 2894-2904, November 2004.
  9. Y. C. Eldar and N. Merhav, ``Robust linear estimation under a minimax MSE-ratio criterion,'' IEEE Trans. Signal Processing, vol. 53, no. 4, pp. 1335-1347, April 2005.
  10. G. Bukai and N. Merhav, ``Channel estimation using feedback,'' Proc. ISIT 2008, pp. 1243-1247, Toronto, Canada, July 2008.
  11. N. Merhav, D. Guo, and S. Shamai (Shitz), ``Statistical physics of signal estimation in Gaussian noise: theory and examples of phase transitions,'' IEEE Trans. on Inform. Theory, vol. 56, no. 3, pp. 1400-1416, March 2010.
  12. N. Merhav, ``Optimum estimation via gradients of partition functions and information measures: a statistical-mechanical perspective,'' IEEE Trans. on Inform. Theory, vol. 57, no. 6, pp. pp.\ 3887--3898, June 2011.
  13. N. Merhav, ``On optimum strategies for minimizing exponential moments of a loss function,'' Communications in Information and Systems, vol. 11, no. 4, pp. 343-368, 2011.
  14. W. Huleihel and N. Merhav, ``Analysis of mismatched estimation errors using gradients of partition functions,'' IEEE Trans. Inform. Theory,, vol. 60, no. 4, pp. 2190-2216, April 2014.
  15. W. Huleihel and N. Merhav, ``Asymptotic MMSE analysis under sparse representation modeling,'' Signal Processing, vol. 131, pp. 320-332, February 2017.
  16. N. Merhav, ``Lower bounds on exponential moments of the quadratic error in parameter estimation,'' IEEE Trans. Inform. Theory, vol. 64, no. 12, pp. 7636-7648, December 2018.
  17. N. Merhav, ``Optimal correlators for detection and estimation in optical receivers,'' IEEE Trans. Inform. Theory, vol. 67, no. 8, pp. 5200-5210, August 2021.
  18. N. Merhav, ``Optimal correlators and waveforms for mismatched detection,'' IEEE Trans. Inform. Theory, vol. 68, no. 12, pp. 8342-8354, December 2022.
Parameter Modulation and Estimation
  1. N. Merhav, ``Threshold effects in parameter estimation as phase transitions in statistical mechanics,'' IEEE Trans. on Inform. Theory, vol. 57, no. 10, pp. 7000-7010, October 2011.
  2. N. Merhav, ``Data processing inequalities based on a certain structured class of information measures with application to estimation theory,'' IEEE Trans. Inform. Theory, vol. 58, no. 8, pp. 5287-5301, August 2012.
  3. N. Merhav, ``On optimum parameter modulation-estimation from a large deviations perspective,'' IEEE Trans. Inform. Theory, vol. 58, no. 12, pp. 7215-7225, December 2012.
  4. N. Merhav, ``Exponential error bounds on parameter modulation-estimation for discrete memoryless channels,'' IEEE Trans. Inform. Theory,, vol. 60, no. 2, pp. 832-841, February 2014.
  5. N. Weinberger and N. Merhav, ``Lower bounds on parameter modulation-estimation under bandwidth constraints,'' IEEE Trans. Inform. Theory,, vol. 63, no. 6, pp. 3854-3874, June 2017.
  6. A. Unsal, R. Knopp, and N. Merhav, ``Converse bounds on modulation-estimation performance for the Gaussian multiple-access channel,'' IEEE Trans. Inform. Theory, vol. 64, no. 2, pp. 1217-1230, February 2018.
  7. N. Merhav, ``Trade-offs between weak-noise estimation performance and outage exponents in nonlinear modulation,'' IEEE Trans. Inform. Theory, vol. 65, no. 8, pp. 5189-5196, August 2019.
  8. N. Merhav, ``Weak-noise modulation-estimation of vector parameters,'' IEEE Trans. Inform. Theory, vol. 66, no. 5, p. 3268-3276, May 2020.
  9. N. Merhav, ``Trade-offs between weak-noise performance and probability of anomaly in parameter estimation from noisy chaotic signals,'' submitted for publication, August 2023.
  10. A. Khina and N. Merhav, ``Modulation and estimation with a helper,'' submitted for publication, September 2023.