Department of
Electrical and
Computer Engineering
MSN 1G5
George Mason University
4400 University Drive
Fairfax, VA 22030-4444
Email: yephraim@gmu.edu
To contact
me please use:
yephraim@gmu.edu.
Yariv
Ephraim received the B.Sc. Cum Laude, the M.Sc.
and the D.Sc. degrees in Electrical Engineering in 1977, 1979 and 1984,
respectively, all from the Technion-Israel
Institute of Technology, Haifa, Israel.
During 1979-1981 he was a researcher at RAFAEL, Israel. During 1984-1985
he was a Rothschild
Post-Doctoral Fellow at the Information Systems Laboratory, Stanford University, Palo Alto, CA. During 1985-1993 he was a Member of Technical
Staff at the Information Principles Research Laboratory, AT&T Bell Labs, Murray Hill, NJ. In 1991 he joined George Mason University, Fairfax, VA, where he
currently is Professor of Electrical and Computer Engineering. He is a co-recipient of the 1999-2000 EURASIP
Best Paper Award; a co-recipient of
the 2020 IEEE Signal Processing Society Sustained
Impact Paper Award; and a co-recipient of the IEEE ICC-2021
Best Paper Award. He was elected Fellow of the IEEE in 1994.
From 2006 to 2009 he was Associate Editor of the IEEE Transactions on
Audio, Speech and Language Processing.
He currently serves on the Editorial Board of Foundations and Trends in
Signal Processing. Yariv Ephraim's primary
research interests are in Statistical Signal Processing. His recent research work has focused on
signal and parameter estimation of partially observable bivariate Markov
processes in discrete and continuous time.
His earlier research has focused on the development of parametric and
non-parametric minimum mean squared error speech
enhancement systems.
ECE 460
Communication and Information
Theory
ECE 528
Introduction to Random
Processes in ECE
ECE 463
Introduction to Random
Processes in ECE
ECE 630
Statistical Communication Theory
ECE 728
Random Processes in
Electrical and Computer
Engineering
ECE 664 (formerly ECE 734) Detection
and Estimation Theory
(To be offered in Fall 2022)
ECE 735
Data Compression
ECE 751
Information Theory
ECE 752
Spectral Estimation
Selected Talks
·
My presentation on Hidden Markov
Processes at the XXXVIme Journes de Statistique, Montpellier, France,
26 May 2004.
Selected Publications (Copyright Notice) Google Citations
·
N. Etemadi
Rad, Y. Ephraim, and
B.L. Mark, Delay network
tomography using a
partially observable bivariate
Markov chain, IEEE/ACM Trans.
on Networking, July 2017 (online at
IEEE Xplore).
·
Y. Sun, B.
L. Mark and Y.
Ephraim, Collaborative Spectrum
Sensing via Online
Estimation of Hidden
Bivariate Markov Models,
IEEE Trans.
on Wireless Communications, pp.
5430-5439, April 2016.
·
Y. Sun, B.
L. Mark, and
Y. Ephraim, Online parameter
estimation for temporal
spectrum sensing, IEEE Trans.
on Wireless Communications, vol. 14, no.
8, pp. 4105-4114, Aug.
2015.
·
Y. Ephraim
and B. L.
Mark, Causal recursive
parameter estimation for
discrete-time hidden bivariate
Markov chains,
IEEE Trans.
on Signal Processing, vol.
63, pp. 2108-2117, April 2015.
·
B. L. Mark, and Y. Ephraim, Explicit causal
recursive estimators for
continuous-time bivariate Markov
chains, IEEE
Trans. on Signal
Processing, vol. 62, pp. 2709-2718, May
2014.
·
T. Nguyen, B.
L. Mark, and
Y. Ephraim, Spectrum sensing
using a hidden
bivariate Markov model,
IEEE Trans.
on Wireless Communications, vol. 12, pp.
4582-4591, Sept. 2013.
·
Y. Ephraim
and B. L. Mark, Bivariate Markov
processes and their
estimation, Foundations and
Trends in Signal
Processing, vol. 6, no.
1, pp. 1-95, 2013.
·
Y. Ephraim
and B. L. Mark, Consistency of
maximum likelihood parameter
estimation for bivariate
Markov chains, Stochastic Models,
2013, 29, 89-111.
·
B. L.
Mark and Y.
Ephraim, An EM
algorithm for continuous-time bivariate
Markov chains, Computational Statistics
and Data Analysis, 2013,
57, 504-517.
·
Y. Ephraim
and B. L. Mark, Explicit forward
recursive estimators for
Markov modulated Markov
processes, Stochastic Models,
2012, 28:3, 359-387.
·
Y. Ephraim
and B. L. Mark, On forward
recursive estimation for
bivariate Markov chains,
Information Sciences and
Systems, CISS, Mar.
2012.
·
Y. Ephraim
and M. Tinston, Iterative Schur
Complement and Multistage
Wiener Filtering, SIAM.
J. Matrix Anal.
& Appl. Vol.
31, Issue 4,
pp. 2222-2238 (2010)
·
Y. Ephraim
and W. J.
J. Roberts, An EM
Algorithm for Markov
modulated Markov Processes, IEEE
Trans. Sig. Proc.,
vol. 57, pp.
463-470, Feb. 2009.
·
W. J.
J. Roberts and
Y. Ephraim, An EM
Algorithm for Ion-Channel
Current Estimation, IEEE
Trans. Sig. Proc.,
vol. 56, pp.
26-33, Jan. 2008.
·
W. J.
J. Roberts, Y.
Ephraim, and E. Dieguez, On Ryden’s EM
Algorithm for Estimating
MMPP’s, IEEE Sig.
Proc. Let., vol.
13, pp. 373-376, June
2006.
·
Y. Ephraim
and I. Cohen, Recent Advancements in
Speech Enhancement, The
Electrical Engineering Handbook,
CRC Press, 2006.
·
Y. Ephraim
and W. J.
J. Roberts, On Second-Order Statistics
of Log-Periodogram with
Correlated Components, IEEE
Sig. Proc. Let., vol. 12, pp.
625-628, Sep.
2005.
·
Y. Ephraim, H.
Lev-Ari and W.
J. J. Roberts, A brief
survey of Speech
Enhancement, The Electronic
Handbook, CRC Press,
April 2005.
·
W. J.
J. Roberts, Y.
Ephraim, and H.
W. Sabrin, Speaker
classification using composite
hypothesis testing and
list decoding, IEEE Trans.
Speech and Audio
Proc., vol. 13, pp.
211-219, Mar. 2005.
·
Y. Ephraim
and W. J.
J. Roberts, Revisiting Autoregressive Hidden
Markov Modeling of
Speech Signals, IEEE
Sig. Proc. Let., vol. 12, pp. 166- 169, Feb. 2005.
·
H. Lev-Ari
and Y. Ephraim,
Extension of
the signal subspace
speech enhancement approach
to colored noise,
IEEE Sig. Proc.
Let., vol. 10, pp. 104-106, April 2003.
·
Y. Ephraim
and N. Merhav, Hidden Markov
processes, IEEE Trans.
Inform. Theory, vol. 48, pp.
1518-1569, June 2002.
·
Y. Ephraim
and W. J.
J. Roberts, On preprocessing for
mismatched classification of
Gaussian signals, IEEE
Trans. Inform. Theory, vol. 47, pp.
1251 -1256, March 2001.
·
W. J.
J. Roberts
and Y. Ephraim, Hidden Markov
modeling of speech
using Toeplitz covariance
matrices, Speech Communication, vol.
31, pp. 1-14, 2000.
·
K. L. Bell, Y. Ephraim, and
H. L. Van Trees, A Bayesian
approach to robust
adaptive beamforming, IEEE
Trans. on Signal
Processing, vol. 48, pp. 386-398, Feb.
2000.
·
Y. Ephraim
and M. Rahim, On second
order statistics and
linear estimation of
cepstral coefficients, IEEE
Trans. on Speech
and Audio Processing, vol. 7, pp.
162-176, March 1999.
·
K. Bell, Y.
Steinberg, Y. Ephraim
and H. L.
Van Trees, Extended Ziv-Zakai lower
bound for vector
parameter estimation, IEEE
Trans. Inform. Theory, vol. 43, pp.
624-637, March 1997.
·
K. Bell, Y.
Ephraim and H.
L. Van Trees, Explicit Ziv-Zakai lower
bounds for bearing
estimation, IEEE Trans.
Signal Processing, vol. 44, pp.
2810-2824, Nov. 1996.
·
Y. Ephraim, N.
Merhav, and H.
L. Van Trees, Min-norm interpretations and
consistency of MUSIC,
MODE and ML,
IEEE Trans. Signal
Processing, vol. 43, pp.
2937-2942, Dec. 1995.
·
Y. Ephraim
and H. L.
Van Trees, A signal
subspace approach for
speech enhancement, IEEE
Trans. Speech and
Audio Processing, vol. 3, pp.
251-266, July 1995.
·
Y. Ephraim, Statistical model
based speech enhancement
systems, IEEE Proc.,
vol. 80, pp.
1526-1555, Oct. 1992.
·
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. IT-38, pp.1709-1724, Nov.
1992.
·
Y. Ephraim, Gain adapted
hidden Markov models
for recognition of
clean and noisy
speech, IEEE Trans.
Signal Processing, vol. SP-40, pp.
1303-1316, June 1992.
·
Y. Ephraim, A Bayesian
estimation approach for
speech enhancement using
hidden Markov models,
IEEE Trans. Signal
Processing, vol. SP-40, pp.
725-735, April 1992.
·
Y. Ephraim,
State dependent
dynamical system model
for speech signals, 1992
Conference on Information
Sciences and Systems, pp.
595-600, Princeton, Mar.
1992.
·
N. Merhav and
Y. Ephraim, A Bayesian
classification approach with
application to speech
recognition, IEEE Trans.
Signal Processing, vol. SP-39, pp.
2157-2166, Oct. 1991.
·
N. Merhav and
Y. Ephraim, Hidden Markov
modeling using a
dominant state sequence
with application to
speech recognition, Computer, Speech,
and Language, vol.
5, no. 4, pp.
327-339, Oct. 1991.
·
Ljolje, Y. Ephraim, and
L. R. Rabiner, Estimation of
hidden Markov model
parameters by minimizing
empirical error rate, IEEE
Int. Conf. on Acoust.,
Speech, Signal Processing, pp.
709-712, Albuquerque, Apr.
1990.
·
Y. Ephraim
and L. R. Rabiner, On the
relations between modeling
approaches for speech
recognition, IEEE Trans.
Inform. Theory, vol.
IT-36, pp. 372-380, Mar.
1990.
·
Y. Ephraim, D.
Malah, and B.-H.
Juang, On the
application of hidden
Markov models for
enhancing noisy speech,
IEEE Trans. Acoust. Speech, Signal Processing, vol.
ASSP-37, pp. 1846-1856, Dec.
1989.
·
Y. Ephraim, A.
Dembo, and L. R. Rabiner, A minimum
discrimination information approach
for hidden Markov
modeling, IEEE Trans.
Inform. Theory, vol. IT-35, pp.
1001-1013, Sept. 1989.
·
Y. Ephraim, H.
Lev-Ari, and R.
M. Gray, Asymptotic minimum
discrimination information measure
for asymptotically weakly
stationary processes, IEEE
Trans. Inform. Theory, vol. IT-34, pp.
1033-1040, Sept. 1988.
·
Y. Ephraim
and R. M. Gray, A unified
approach for encoding
clean and noisy
sources by means
of waveform and
autoregressive model vector
quantization, IEEE Trans.
Inform. Theory, vol. IT-34, pp.
826-834, July 1988.
·
Y. Ephraim
and D. Malah, Speech enhancement
using a minimum
mean square error
log-spectral amplitude estimator, IEEE
Trans. on Acoust., Speech,
Signal Processing, vol. ASSP-33, pp.
443-445, Apr. 1985.
·
Y. Ephraim
and D. Malah, Speech enhancement
using a minimum
mean square error
short-time spectral amplitude
estimator, IEEE Trans.
on Acoust.,
Speech, Signal Processing,
vol. ASSP-32, pp.
1109-1121, Dec. 1984.