Journal Publications
Y. Mazor, I. E. Berman, and T. Routtenberg,
“Bayesian Cramér-Rao bound with Mixed-resolution Data,” Submitted Oct., 2024
G. Morgenstern and T. Routtenberg,
“Theoretical Guarantees for Sparse Graph Signal Recovery,”
Submitted Oct., 2024
Y. Gabay, N. Shlezinger, T. Routtenberg, Y. Ghasempour, G. C. Alexandropoulos, and Y. C. Eldar,
“Wideband THz Multi-User Downlink Communications with Leaky Waveguide Antennas,”
Submitted, July 2024.
G. Morgenstern and T. Routtenberg,
“Recovery of Sparse Graph Signals,”
Accepted to IEEE Transactions on Signal Processing
Nov. 2024.
I. Buchnik, G. Sagi, N. Leinwand, Y. Loya, N. Shlezinger, and T. Routtenberg,
“GSP-KalmanNet: Tracking Graph Signals via Neural-Aided Kalman Filtering,”
IEEE Transactions on Signal Processing
vol. 72, pp. 3700-3716, 2024
M. Halihal, T. Routtenberg, and V.H. Poor,
“Estimation of Complex-Valued Laplacian Matrices for Topology Identification in Power Systems,”
IEEE Transactions on Signal Processing
vol. 72, pp. 3626-3640, 2024
N. Harel and T. Routtenberg,
“Non-Bayesian Post-Model-Selection Estimation as Estimation Under Model Misspecification,”
IEEE Transactions on Signal Processing
vol. 72, pp. 3641-3657, 2024
L. Dabush and T. Routtenberg,
“Verifying the Smoothness of Graph Signals: A Graph Signal Processing Approach,”
IEEE Transactions on Signal Processing
Vol. 72, pp. 4349-4365, 2024
T. Weiss, T. Routtenberg, J. Ostrometzky, and H. Messer,
“Intensity Estimation After Detection for Accumulated Rainfall Estimation”, Frontiers in Signal Processing, 4:1291878. (Jan. 2024).
N. Zimerman, M. Khatib, Y. Ben-Horin, Y. Radzyner, J. D. Rosenblatt, and T. Routtenberg,
“Geometry Design for DOA Estimation in Seismic 2D-Arrays: Simulation Study,”
IEEE Access vol. 12, pp. 35827-35843, 2024.
G. Morgenstern, J. Kim, J. Anderson, G. Zussman, and T. Routtenberg, “Protection Against Graph-Based False Data Injection Attacks on Power Systems”,
IEEE Trans. Control of Network Systems (Jan. 2024).
G. Sagi and T. Routtenberg,
“MAP Estimation of Graph Signals,”
IEEE Transactions on Signal Processing
vol. 72, pp. 463-479, 2024.
I. Buchnik, D. Steger, G. Revach, R. J. G. van Sloun, T. Routtenberg, and N. Shlezinger,
“Latent-KalmanNet: Learned Kalman Filtering for Tracking High-Dimensional Signals,”
IEEE Transactions on Signal Processing
vol. 72, pp. 352-367, 2024.
J. P. Merkofer, G. Revach, N. Shlezinger, T. Routtenberg, and R. J. G. van Sloun,
“DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm”,
IEEE Transactions on Vehicular Technology
vol. 73, no. 2, pp. 2771-2785, Feb. 2024.
E. Nitzan, T. Routtenberg, and J. Tabrikian, “Barankin-Type Bound for Constrained Parameter Estimation”,
IEEE Transactions on Signal Processing
vol. 71, pp. 3929-3944, 2023.
N. Shlezinger and T. Routtenberg,
“Discriminative and Generative Learning for Linear Estimation of Random Signals,” (Lecture notes),
IEEE Signal Processing Magazine
vol. 40, no. 6, pp. 75-82, Sept. 2023.
A. Amar and T. Routtenberg,
“Widely-Linear MMSE Estimation of Complex-Valued Graph Signals”,
IEEE Transactions on Signal Processing, vol. 71, pp. 1770-1785, 2023.
L. Dabush, A. Kroizer, and T. Routtenberg,
“State Estimation in Partially Observable Power Systems via Graph Signal Processing Tools”,
Sensors, 23, 1387, 2023.
G. Morgenstern and T. Routtenberg,
“Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks in Power Systems”,
IEEE Access, 2022.
T. Routtenberg and J. Tabrikian,
“Bayesian Periodic Cramér-Rao Bound”,
IEEE Signal Processing Letters, 2022.
S. Cohen, T. Routtenberg, and L. Tong,
“Non-Bayesian Parameter Estimation of the Probability of the Missing Mass”,
IEEE Transactions on Signal Processing,
vol. 70, pp. 3709-3725, 2022.
A. Kroizer, T. Routtenberg, and Y. C. Eldar,
“Bayesian Estimation of Graph Signals”,
IEEE Transactions on Signal Processing,
vol. 70, pp. 2207-2223, March 2022.
I. E. Berman and T. Routtenberg,
“Partially Linear Bayesian Estimation Using Mixed-Resolution Data”,
IEEE Signal Processing Letters,
vol. 28, pp. 2202-2206, 2021.
I. E. Berman and T. Routtenberg,
“Resource Allocation and Dithering of Bayesian Parameter Estimation Using Mixed-Resolution Data”,
IEEE Transactions on Signal Processing,
vol. 69, pp. 6148-6164, 2021.
Video Presentation
S. Shaked and T. Routtenberg,
“Identification of Edge Disconnections in Networks Based on Graph Filter Outputs”,
IEEE Transactions on Signal and Information Processing over Networks,
vol. 7, pp. 578-594, 2021.
Video Presentation
E. Meir and T. Routtenberg,
“Cramér-Rao Bound for Estimation After Model Selection and its Application to Sparse Vector Estimation”,
IEEE Transactions on Signal Processing,
vol. 69, pp. 2284-2301, 2021.
Presentation
T. Weiss, T. Routtenberg, and H. Messer,
“Total Performance Evaluation of Intensity Estimation after Detection”,
Signal Processing,
vol. 183, pp. 1-8, 2021.
(Weinstein Award to student paper in signal processing)
T. Routtenberg,
“Non-Bayesian Estimation Framework for Statistical Signal Recovery on Graphs”,
IEEE Transactions on Signal Processing,
vol. 69, pp. 1169-1184, 2021.
Video Presentation
N. Harel and T. Routtenberg,
“Bayesian Estimation After Model Selection”,
IEEE Signal Processing Letters,
vol. 28, pp. 175-179, 2021.
Video Presentation
E. Levy and T. Routtenberg,
“Low-Complexity Detection of Small Frequency Deviations by the Generalized LMPU Test”,
Signal Processing,
Vol. 180, pp. 1-8, 2021.
N. Harel and T. Routtenberg,
“Low-Complexity Methods for Estimation After Parameter Selection”,
IEEE Transactions on Signal Processing,
vol. 68, pp. 1152-1167, 2020.
Code
E. Drayer and T. Routtenberg,
“Detection of False Data Injection Attacks in Smart Grids based on Graph Signal Processing”,
IEEE Systems Journal,
vol. 14, no. 2, pp. 1886-1896, June, 2020.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Cramér-Rao Bound under Norm Constraint”,
IEEE Signal Processing Letters,
vol. 26, no. 9, pp. 1393-1397, Sept. 2019.
S. Grotas, Y. Yakoby, I. Gera, and T. Routtenberg,
“Power Systems Topology and State Estimation by Graph Blind Source Separation”,
IEEE Transactions on Signal Processing
vol. 67, no. 8, pp. 2036-2051, Apr. 2019.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Cramér-Rao Bound for Constrained Parameter Estimation Using Lehmann-Unbiasedness”,
IEEE Transactions on Signal Processing
vol. 67, no. 3, pp. 753-768, Feb. 2019.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Bobrovsky-Zakai-Type Bound for Periodic Stochastic Filtering”,
IEEE Signal Processing Letters,
vol. 25, no. 10, pp. 1460-1464, Oct. 2018.
T. Routtenberg and Y. C. Eldar,
“Centralized Identification of Imbalances in Power Networks with Synchrophasor Data,”
IEEE Transactions on Power Systems,
vol. 33, no. 2, pp. 1981-1992, March 2018.
T. Routtenberg, R. Concepcion, and L. Tong,
“PMU-based Detection of Voltage Imbalances with Tolerance Constraints”,
IEEE Transactions on Power Delivery
vol. 32, no. 1, pp. 484-494, Feb. 2017.
T. Routtenberg and L. Tong,
“Estimation After Parameter Selection: Performance Analysis and Estimation Methods,”
IEEE Transactions on Signal Processing, vol. 64, no. 20, pp. 5268-5281, Oct. 2016.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Stochastic Filtering Using Periodic Cost Functions,”
The Journal of Advances in Information Fusion,
Special issue on estimation involving directional quantities, vol. 11, pp. 123-137, Dec. 2016.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“A New Class of Bayesian Cyclic Bounds for Periodic Parameter Estimation,”
IEEE Transactions on Signal Processing, vol. 64, no. 1, pp. 229-243, Jan., 2016.
T. Routtenberg, Y. Xie, R. M. Willett, and L. Tong,
“PMU-based Detection of Imbalance in Three-Phase Power Systems”,
IEEE Transactions on Power System, vol. 30, no. 4, pp. 1966-1976, July 2015.
T. Routtenberg and J. Tabrikian,
“Cyclic Barankin Bounds for Non-Bayesian Periodic Parameter estimation”,
IEEE Transactions on Signal Processing, vol. 62, no. 13, pp. 3321-3336, July, 2014.
T. Routtenberg and L. Tong,
“Joint Frequency and Phasor Estimation Under the KCL Constraint”,
IEEE Signal Processing Letters,
vol. 20, no.6, pp. 575-578, June 2013.
T. Routtenberg and J. Tabrikian,
“Non-Bayesian Periodic Cramér-Rao Bound”,
IEEE Transactions on Signal Processing,
vol. 61, no. 4, Feb. 2013.
T. Routtenberg and J. Tabrikian,
“A General Class of Outage Error Probability Lower Bounds in Bayesian Parameter Estimation”,
IEEE Transactions on Signal Processing,
vol. 60, no. 5, pp. 2152-2166, May 2012.
T. Routtenberg and J. Tabrikian,
“Bayesian Parameter Estimation using Periodic Cost Functions”,
IEEE Transactions on Signal Processing,
vol. 60, no. 3, pp. 1229-1240, March 2012.
T. Routtenberg and J. Tabrikian,
“Blind MIMO-AR System Identification and Source Separation with Finite-Alphabet”,
IEEE Transactions on Signal Processing,
vol. 58, no. 3, pp. 990-1000, March 2010.
T. Routtenberg and J. Tabrikian, “MIMO-AR System Identification and Blind Source Separation for GMM-distributed Sources”,
IEEE Transactions on Signal Processing, vol. 57, no. 5, pp. 1717-1730, May 2009.
D. Offen, Y. Barhum, Y. S. Levy, A. Burshtein, H. Panet, T. Cherlow, and E. Melamed,
“Intrastriatal Transplantation of Mouse Bone Marrow-derived Stem Cells Improves Motor Behavior in a Mouse Model of Parkinson's disease”,
J. Neural Transm. Suppl, no. 72, pp. 133-143, 2007.
I. Kan, T. Ben-Zur, Y. Barhum, Y. S. Levy, A. Burstein, T. Cherlow, S. Bulvik, E. Melamed, and D. Offen,
“Dopaminergic Differentiation of Human Mesenchymal Stem Cells-Utilization of Bioassay for Tyrosine Hydroxylase Expression”,
Neurosci Lett., vol. 419, pp. 28-33, Apr. 13, 2007.
N. R. Blondheim, Y. S. Levy, T. Ben-Zur, A. Burshtein, T. Cherlow, I. Kan, R. Barzilai, M. Bahat-Stromza, Y. Barhum, S. Bulvik, E. Melamed, and D. Offen,
“Human Mesenchymal Stem Cells Express Neural Genes, Suggesting a Neural Predisposition”,
Stem Cells Dev.
Apr. 15(2), pp. 141-164, 2006.
Other Publications
E. V. Belmega et al.,
“Guest Editorial: Pervasive, Efficient, and Smart Signal Processing for IoT,”,
IEEE Internet of Things Magazine,
vol. 5, no. 4, pp. 54-57, December 2022.
T. Routtenberg, A. Carini, E. Chouzenoux, P. Pal, J. C. M. Bermudez, and L. Marcenaro,
“Fight the Pandemic: Highlights from the 2020 IEEE Five-Minute Video Clip Contest (Column)”,
IEEE Signal Processing Magazine,
vol. 38, no. 2, pp. 138-143, March 2021.
E. Levy and T. Routtenberg,
Supplemental Data for the Paper “Low-Complexity Detection of Small Frequency Deviations by the Generalized LMPU Test”, Data in Brief, Vol. 34, 2021.
Conference Publications
Y. Medvedovsky, E. Treister, and T. Routtenberg,
“Efficient Graph Laplacian Estimation by Proximal Newton”,
International Conference on Artificial Intelligence and Statistics (AISTAT 2024)
PMLR 238:1171-1179, 2024.
Y. Gabay, N. Shlezinger, T. Routtenberg, Y. Ghasempour, G. C. Alexandropoulos, Y. C. Eldar,
“Leaky Waveguide Antennas for Downlink Wideband Thz Communications,”
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024)
pp. 9111-9115, April 2024
M. Halihal and T. Routtenberg,
“Cramér-Rao Bound for Admittance Matrix Estimation Under Laplacian Constraints,” accepted to IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024)
pp. 9871-9875, April 2024
L. Dabush and T. Routtenberg,
[https:ieeexplore.ieee.orgdocument10446697 “Kalman Filter for Tracking Network Dynamic,”
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024).
pp. 13216-13220, April 2024.
M. Zhao, G. Revach, T. Routtenberg, and N. Shlezinger,
“NUV-DoA: NUV Prior-based Bayesian Sparse Reconstruction with Spatial Filtering for Super-Resolution DoA Estimation,”
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024).
pp. 8676-8680, April 2024.
M. Khatib, N. Harel, Y. Ben-Horin, Y. Radzyner, and T. Routtenberg, “Cyclic Misspecified Cramér-Rao Bound for Periodic Parameter Estimation,”
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024).
pp. 9911-9915, April 2024.
G. Morgenstern and T. Routtenberg,
“Sparse Graph Signal Recovery by Graph-Based Multiple Generalized Information Criterion (GM-GIC),”
IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2023).
G. Morgenstern, L. Dabush, J. Kim, J. Anderson, G. Zussman, and T. Routtenberg,
“Detection of False Data Injection Attacks in Power Systems using a Secured Sensors-Informed Graph-Based Method,”
Accepted to 25th International Symposium on Stabilization, Safety, and Security of Distributed Systems (SSS 2023).
M. Khatib, Y. Ben-Horin, Y. Radzyner, J. D. Rosenblatt, and T. Routtenberg,
“Periodic Fisher-Scoring Algorithm with Applications for DOA Estimation in Seismic Arrays,”
FUSION 2023
(Invited to Special Session on Directional statistics).
A. Sridhar, T. Routtenberg, and V. H. Poor
“Quickest Inference of Susceptible-Infected Cascades in Sparse Networks”
Accepted to ISIT 2023
G. Sagi, N. Shlezinger, and T. Routtenberg
“Extended Kalman Filter for Graph Signals in Nonlinear Dynamic Systems,”
Accepted to IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023)
(Invited to Special Session on Graphical Inference and Modeling in Dynamical Systems)
I. Buchnik, D. Steger, G. Revach, R. J. G. van Sloun, T. Routtenberg, and N. Shlezinger
“Learned Kalman Filtering in Latent Space with High-Dimensional Data,”
Accepted to IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023)
L. Dabush, N. Shlezinger, and T. Routtenberg,
“Generative Versus Discriminative Data-Driven Graph Filtering of Random Graph Signals,”
Accepted to CISS 2023
L. Dabush and T. Routtenberg,
“Detection of False Data Injection Attacks in Unobservable Power Systems by Laplacian Regularization,”
in Proc. of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM),
pp. 415-419 June, 2022
M. Halihal and T. Routtenberg,
“Estimation of the Admittance Matrix in Power Systems under Laplacian and Physical Constraints,”
in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022),
May, 2022, pp. 5972-5976.
Video Presentation
N. Harel and T. Routtenberg,
“Post-Parameter-Selection Maximum-Likelihood Estimation,”
IEEE Workshop on Statistical Signal Processing (SSP 2021)
N. Zimerman, J. D. Rosenblatt, and T. Routtenberg,
“Colored Noise in DOA Estimation from Seismic Data: an Empirical Study,” Asilomar Conference on Signals, Systems, and Computers, Oct. 2020.
A. Kroizer, Y. C. Eldar, and T. Routtenberg,
“Modeling and Recovery of Graph Signals and Difference-Based Signals,”
GlobalSIP 2019.
E. Drayer and T. Routtenberg,
“Brief Announcement: Cyber Attack Localization in Smart Grids by Graph Modulation,”
CSCML 2019.
E. Drayer and T. Routtenberg,
“Intrusion Detection in Smart Grid Measurement Infrastructures based on Principal Component Analysis,”
IEEE PES PowerTech, Milano 2019.
E. Drayer and T. Routtenberg,
“Detection of False Data Injection Attacks in Power Systems with Graph Fourier Transform,”
GlobalSIP
Nov. 2018, pp. 890-894.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Multivariate Bayesian Cramér-Rao-Type Bound for Stochastic Filtering Involving Periodic States,”
Proc. of the International Conference on Information Fusion
July 2018, pp. 179-186.
E. Meir and T. Routtenberg,
“Selective Cramér-Rao Bound for Estimation After Model Selection,”
Proc. of the IEEE Workshop on Statistical Signal Processing (SSP 2018)
June 2018, pp. 757-761.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Limitations of Constrained CRB and an Alternative Bound,”
Proc. of the IEEE Workshop on Statistical Signal Processing (SSP 2018)
June 2018, pp. 673-677.
(Best Student Paper Award).
I. Gera*, Y. Yakoby*, and T. Routtenberg,
“Blind Estimation of States and Topology (BEST) in
Power Systems,”
GlobalSIP
Nov. 2017, pp. 1080-1084.
(Invited to the Symposium on Information Processing and Optimization for Smart Grids).
*Equally contributors
N. Harel and T. Routtenberg,
“Non-Bayesian Estimation with Partially Quantized Observations,”
in Proc. of the DSP 2017,
Aug. 2017, pp. 1-5.
T. Routtenberg and Y. Xie,
“PMU-based Online Change-Point Detection of Imbalance in Three-Phase Power Systems,”
in Proc. of the ISGT 2017,
April 2017, pp. 1-5.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Optimal Biased Estimation Using Lehmann-Unbiasedness,”
in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017),
Mar. 2017, pp. 4496-4500.
(Best Student Paper Award).
A. Salman, Y. Cohen, L. Simchon, T. Routtenberg, R. Rabinovici,
“Optimal Switching in a Three-Level Inverter: an Analytical Approach,”
in Proc. of the International Conference on the Science of Electrical Engineering (2016 ICSEE),
Nov. 2016, pp. 1-5.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Mean-Cyclic-Error Lower Bounds via Integral Transform of Likelihood-Ratio Function,”
in Proc. of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2016),
July 2016, pp. 1-5.
T. Routtenberg and J. Tabrikian,
“Cyclic Cramér-Rao-type Bounds for Periodic Parameter Estimation,”
in Proc. of the International Conference on Information Fusion 2016,
July 2016, pp. 1797-1804.
(Invited to Special Session on Directional Estimation)
T. Routtenberg,
“Two-Stage Estimation After Parameter Selection,”
in Proc. of the IEEE Workshop on Statistical Signal Processing (SSP 2016),
June 2016, pp. 1-5.
E. Nitzan, T. Routtenberg, and J. Tabrikian,
“Cyclic Bayesian Bounds for Filtering in Periodic State Space,”
in Proc. of the International Conference on Information Fusion 2015, July 2015, pp.734-741.
(Invited to Special Session on Directional Estimation)
T. Routtenberg and L. Tong,
“Networked Detection of Voltage Imbalances for Three-Phase Power System,”
in Proc. of the IEEE International Symposium on Industrial Electronics (ISIE 2015),
June 2015, pp. 1345-1350.
(Invited to Special Session on Signal Processing for Smart Grids Monitoring, State Estimation and Fault Detection)
R. Conception, T. Routtenberg, and L. Tong,
“Local Detection of Voltage Unbalance in Three-Phase Power Systems Based on PMU Output,”
in Proc. of the sixth Conference on Innovative Smart Grid Technologies (ISGT 2015), Feb. 2015, pp. 1-5.
T. Routtenberg and L. Tong,
“The Cramér-Rao Bound for Estimation-after-Selection,”
in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014),
May 2014, pp. 414-418.
T. Routtenberg and L. Tong,
“Joint Frequency and Phasor Estimation in Unbalanced Three-Phase Power Systems,”
in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014),
May 2014, pp. 3006-3010.
E. Nitzan, J. Tabrikian, and T. Routtenberg,
“Bayesian cyclic bounds for periodic parameter estimation”,
Fifth IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2013), Dec. 2013, pp. 308-311. (Best Student Paper Award)
T. Routtenberg, Y. C. Eldar, and L. Tong,
“Maximum likelihood estimation under partial sparsity constraints”,
Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), May 2013, pp. 6421-6425.
T. Routtenberg and J. Tabrikian,
“Performance bounds for constrained parameter estimation”,
Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2012), pp. 513-516, June 2012.
T. Routtenberg and J. Tabrikian,
“Periodic CRB for non-Bayesian parameter estimation”,
in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), May 2011, pp. 2448-2451.
(Best Student Paper Award)
T. Routtenberg and J. Tabrikian,
“Outage error probability lower bounds in vector parameter estimation”,
in Proc. of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2010), October 2010, pp. 105-108.
T. Routtenberg and J. Tabrikian,
“Optimal Bayesian parameter estimation with periodic criteria”,
in Proc. of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2010), October 2010, pp. 53-56.
T. Routtenberg and J. Tabrikian,
“General classes of Bayesian bounds for outage error probability and MSE”,
in Proc. 2009 IEEE Workshop on Statistical Signal Processing (SSP2009), Aug.-Sep. 2009, pp. 69-72.
T. Routtenberg and J. Tabrikian,
“A general class of lower bounds on the probability of error in multiple hypothesis testing”,
in Proc. of the 25th IEEE Convention of Electrical and Electronics Engineers in Israel, December 2008, pp. 750-754.
T. Routtenberg and J. Tabrikian,
“MIMO-AR system identification and blind source separation using GMM”,
in Proc. Of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007), Apr. 2007, pp. 761-764.
T. Routtenberg and J. Tabrikian,
“Blind source separation for MIMO-AR mixtures using GMM”,
in Proc. of the 24th IEEE Convention of Electrical and Electronics Engineers in Israel, November 2006, pp. 310-314.
Extended Abstracts
M. Halihal and T. Routtenberg,
“Laplacian-Constrained Cramér-Rao Bound for Networks Applications”, Accepted to the Graph Signal Processing Workshop, Delft, June 24-26th, 2024
G. Morgenstern and T. Routtenberg,
“Sparse Recovery of Diffused Graph Signals”,
Accepted to Graph Signal Processing Workshop, Delft, June 24-26th, 2024.
M. Khatib, Y. Ben-Horin, Y. Radzyner, and T. Routtenberg, “New Periodic Fisher Scoring Method for DOA Estimation for Seismic Signals”,
Accepted to the Science and Technology Conference 2023 (SnT2023) of CTBTO.
M. Khatib, J. P. Merkofer, Y. Ben-Horin, Y. Radzyner, G. Revach, R. J. G. van Sloun, N. Shlezinger, and T. Routtenberg, “Azimuth Estimation in Seismic Arrays via Deep Augmented MUSIC Algorithm”,
Accepted to the Science and Technology Conference 2023 (SnT2023) of CTBTO.
N. Harel and T. Routtenberg,
“Bayesian Cramér-Rao Bound for Estimation After Model Selection”,
Asilomar 2020 (Invited to Special Session on “Bayesian Bounds for Stochastic Signal Recovery”)
S. Cohen and T. Routtenberg,
“New Cramér-Rao Lower Bound for Missing-Mass Estimation”, Bernoulli-IMS One World Symposium, 2020 (virtual, August 2020, Special Session on “Limit theorems, large deviations and extremes”).
G. Morgenstern and T. Routtenberg, “Network Constraints Against Cyber attacks in Power Systems”,
Graph Signal Processing Workshop, June 5-7th, 2019.
S. Grotas and T. Routtenberg, “Graph Blind Source Separation with Applications for Power Systems”,
Graph Signal Processing Workshop, June 5-7th, 2019.
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