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IEEE International Conference on Acoustics, Speech, and Signal Processing, vol.4, pp.1797-1800, 1999.","DOI":"10.1109\/ICASSP.1999.758269"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] E. Moulines, P. Duhamel, J.-F. Cardoso, and S. Mayrargue, \u201cSubspace methods for the blind identification of multichannel FIR filters,\u201d IEEE Trans. Signal Process., vol.43, no.2, pp.516-525, 1995.","DOI":"10.1109\/78.348133"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] L. Tong, G. Xu, and T. Kailath, \u201cBlind identification and equalization based on second-order statistics: A time domain approach,\u201d IEEE Trans. Inf. Theory, vol.40, no.2, pp.340-349, 1994.","DOI":"10.1109\/18.312157"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] I. Santamaria, J. Via, and C.C. Gaudes, \u201cRobust blind identification of SIMO channels: A support vector regression approach,\u201d Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.V-673-6, 2004.","DOI":"10.1109\/ICASSP.2004.1327200"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] S.J. Nawaz, K.I. Ahmed, M.N. Patwary, and N.M. Khan, \u201cSuperimposed training-based compressed sensing of sparse multipath channels,\u201d IET Communications, vol.6, no.18, pp.3150-3156, 2012.","DOI":"10.1049\/iet-com.2012.0162"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] B. Gao, Z. Xiao, C. Zhang, D. Jin, and L. Zeng, \u201cSparse\/dense channel estimation with non-zero tap detection for 60-GHz beam training,\u201d IET Communications, vol.8, no.11, pp.2044-2053, 2014.","DOI":"10.1049\/iet-com.2013.0942"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, \u201cCompressed channel sensing: A new approach to estimating sparse multipath channels,\u201d Proc. IEEE, vol.98, no.6, pp.1058-1076, 2010.","DOI":"10.1109\/JPROC.2010.2042415"},{"key":"11","unstructured":"[11] Y. Lin, J. Chen, Y. Kim, and D.D. Lee, \u201cBlind channel identification for speech dereverberation using <i>l<\/i><sub>1<\/sub>-norm sparse learning,\u201d Advances in Neural Information Processing Systems, pp.921-928, 2007."},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] A. A\u00efssa-El-Bey and K. Abed-Meraim, \u201cBlind SIMO channel identification using a sparsity criterion,\u201d Proc. IEEE 9th Workshop on Signal Processing Advances in Wireless Communications, pp.271-275, 2008.","DOI":"10.1109\/SPAWC.2008.4641612"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] Y. Lin and D.D. Lee, \u201cBayesian regularization and nonnegative deconvolution for room impulse response estimation,\u201d IEEE Trans. Signal Process., vol.54, no.3, pp.839-847, 2006.","DOI":"10.1109\/TSP.2005.863030"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] W.U. Bajwa, J. Haupt, G. Raz, and R. Nowak, \u201cCompressed channel sensing,\u201d Proc. 42nd Annual Conference on Information Sciences and Systems, pp.5-10, 2008.","DOI":"10.1109\/CISS.2008.4558485"},{"key":"15","unstructured":"[15] W.H. Tranter, D.P. Taylor, R.E. Ziemer, N.F. Maxemchuk, and J.W. Mark, \u201cCharacterization of randomly time-variant linear channels \u2014 An operation to directional channel,\u201d in The Best of the Best: Fifty Years of Communications and Networking Research, Wiley-IEEE Press, 2007."},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] A.M. Sayeed and B. Aazhang, \u201cJoint multipath-Doppler diversity in mobile wireless communications,\u201d IEEE Trans. Commun., vol.47, no.1, pp.123-132, 1999.","DOI":"10.1109\/26.747819"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] M.L. Malloy and A.M. Sayeed, \u201cRevisiting non-coherent detection in doubly selective multipath,\u201d IEEE Trans. Signal Process., vol.61, no.17, pp.4330-4340, 2013.","DOI":"10.1109\/TSP.2013.2269904"},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] A.A.M. Saleh and R. Valenzuela, \u201cA statistical model for indoor multipath propagation,\u201d IEEE J. Sel. Areas. Commun., vol.5, no.2, pp.128-137, 1987.","DOI":"10.1109\/JSAC.1987.1146527"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] L. Vuokko, V.-M. Kolmonen, J. Salo, and P. Vainikainen, \u201cMeasurement of large-scale cluster power characteristics for geometric channel models,\u201d IEEE Trans. Antennas Propag., vol.55, no.11, pp.3361-3365, 2007.","DOI":"10.1109\/TAP.2007.908844"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] K.E. Themelis, A.A. Rontogiannis, and K.D. Koutroumbas, \u201cA variational Bayes framework for sparse adaptive estimation,\u201d IEEE Trans. Signal Process., vol.62, no.18, pp.4723-4736, 2014.","DOI":"10.1109\/TSP.2014.2338839"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] S. Ji, Y. Xue, and L. Carin, \u201cBayesian compressive sensing,\u201d IEEE Trans. Signal Process., vol.56, no.6, pp.2346-2356, 2008.","DOI":"10.1109\/TSP.2007.914345"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] D. Tse and P. Viswanath, Fundamentals of Wireless Communication, Cambridge University Press, 2005.","DOI":"10.1017\/CBO9780511807213"},{"key":"23","unstructured":"[23] D.P. Wipf, \u201cSparse estimation with structured dictionaries,\u201d Advances in Neural Information Processing Systems, pp.2016-2024, 2011."},{"key":"24","unstructured":"[24] M.E. Tipping, \u201cSparse Bayesian learning and the relevance vector machine,\u201d J. Machine Learning Research, vol.1, pp.211-244, 2001."},{"key":"25","doi-asserted-by":"crossref","unstructured":"[25] J.C. MacKay, \u201cBayesian interpolation,\u201d Neural Computation, vol.4, no.3, pp.415-447,1992.","DOI":"10.1162\/neco.1992.4.3.415"},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] R.G. Baraniuk, \u201cCompressive sensing,\u201d IEEE Signal Process. Mag., vol.24, no.4, pp.118-121, 2007.","DOI":"10.1109\/MSP.2007.4286571"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[27] P. Bello, \u201cCharacterization of randomly time-variant linear channels,\u201d IEEE Trans. Commun., vol.11, no.4, pp.360-393, 1963.","DOI":"10.1109\/TCOM.1963.1088793"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] M.F. Duarte and Y.C. Eldar, \u201cStructured compressed sensing: From theory to applications,\u201d IEEE Trans. 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