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Gaussian belief propagation (BP) is a computationally efficient method to approximate the marginal distribution and has been widely used for inference with high dimensional data as well as distributed estimation in large-scale networks.
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——, “Network-wide distributed carrier frequency offsets estimation and compensation via belief propagation,” IEEE Trans. Signal Process. , vol. 61, no. 23, pp. 5868–5877, 2013
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J. Du and Y. C. Wu, “Fully distributed clock skew and offset estimation in wireless sensor networks,” in 2013 IEEE International Conference on Acoustics, Speech and Signal Processing , 2013, pp. 4499–4503
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P. Som, T. Datta, N. Srinidhi, A. Chockalingam, and B. S. Rajan, “Low-complexity detection in large-dimension MIMO-ISI channels using graphical models,” IEEE Journal of Selected Topics in Signal Processing , vol. 5, no. 8, pp. 1497–1511, 2011
2011
Cited alongside, same era.
F. Lehmann, “Iterative mitigation of intercell interference in cellular networks based on Gaussian belief propagation,” IEEE Trans. Veh. Technol. , vol. 61, no. 6, pp. 2544–2558, July 2012
2012
Cited alongside, same era.
J. Du and Y.-C. Wu, “Distributed clock skew and offset estimation in wireless sensor networks: Asynchronous algorithm and convergence analysis,” IEEE Trans. Wireless Commun. , vol. 12, no. 11, pp. 5908–5917, Nov 2013
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Cited alongside, same era.
2017
Closest in time.
J. Du, S. Ma, Y.-C. Wu, S. Kar, and J. M. Moura, “Convergence analysis of belief propagation for pairwise linear Gaussian models,” in 2017 IEEE Global Conference on Signal and Information Processing , Nov. 14-16, 2017, Montreal, Canada
2017
Closest in time.
J. Du, S. Ma, Y. C. Wu, S. Kar, and J. M. F. Moura, “Convergence analysis of the information matrix in Gaussian belief propagation,” in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , Mar. 5-9, 2017, New Orleans, LA., pp. 4074–4078
2017
Closest in time.