{"type":"conference","citation":{"apa":"Ramírez, D., Vía, J., Santamaría, I., &#38; Scharf, L. L. (2011). Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels. <i>Proc.\\ IEEE Int.\\ Conf.\\ Acoustics, Speech and Signal Process.</i> <a href=\"https://doi.org/10.1109/ICASSP.2011.5947194\">https://doi.org/10.1109/ICASSP.2011.5947194</a>","chicago":"Ramírez, D., J. Vía, I. Santamaría, and L. L. Scharf. “Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels.” In <i>Proc.\\ IEEE Int.\\ Conf.\\ Acoustics, Speech and Signal Process.</i> Prague, Czech Republic, 2011. <a href=\"https://doi.org/10.1109/ICASSP.2011.5947194\">https://doi.org/10.1109/ICASSP.2011.5947194</a>.","mla":"Ramírez, D., et al. “Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels.” <i>Proc.\\ IEEE Int.\\ Conf.\\ Acoustics, Speech and Signal Process.</i>, 2011, doi:<a href=\"https://doi.org/10.1109/ICASSP.2011.5947194\">10.1109/ICASSP.2011.5947194</a>.","ieee":"D. Ramírez, J. Vía, I. Santamaría, and L. L. Scharf, “Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels,” 2011, doi: <a href=\"https://doi.org/10.1109/ICASSP.2011.5947194\">10.1109/ICASSP.2011.5947194</a>.","bibtex":"@inproceedings{Ramírez_Vía_Santamaría_Scharf_2011, place={Prague, Czech Republic}, title={Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2011.5947194\">10.1109/ICASSP.2011.5947194</a>}, booktitle={Proc.\\ IEEE Int.\\ Conf.\\ Acoustics, Speech and Signal Process.}, author={Ramírez, D. and Vía, J. and Santamaría, I. and Scharf, L. L.}, year={2011} }","ama":"Ramírez D, Vía J, Santamaría I, Scharf LL. Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels. In: <i>Proc.\\ IEEE Int.\\ Conf.\\ Acoustics, Speech and Signal Process.</i> ; 2011. doi:<a href=\"https://doi.org/10.1109/ICASSP.2011.5947194\">10.1109/ICASSP.2011.5947194</a>","short":"D. Ramírez, J. Vía, I. Santamaría, L.L. Scharf, in: Proc.\\ IEEE Int.\\ Conf.\\ Acoustics, Speech and Signal Process., Prague, Czech Republic, 2011."},"department":[{"_id":"263"}],"date_created":"2023-01-30T11:51:59Z","doi":"10.1109/ICASSP.2011.5947194","_id":"40835","status":"public","year":"2011","author":[{"last_name":"Ramírez","full_name":"Ramírez, D.","first_name":"D."},{"last_name":"Vía","full_name":"Vía, J.","first_name":"J."},{"last_name":"Santamaría","full_name":"Santamaría, I.","first_name":"I."},{"first_name":"L. L.","last_name":"Scharf","full_name":"Scharf, L. L."}],"user_id":"43497","title":"Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels","publication":"Proc.\\ IEEE Int.\\ Conf.\\ Acoustics, Speech and Signal Process.","abstract":[{"lang":"eng","text":"This work addresses the problem of deciding whether a set of realizations of a vector-valued time series with unknown temporal correlation are spatially correlated or not. Specifically, the spatial correlation is induced by a colored source over a frequency-flat single-input multiple-output (SIMO) channel distorted by independent and identically distributed noises with temporal correlation. The generalized likelihood ratio test (GLRT) for this detection problem does not have a closed-form expression and we have to resort to numerical optimization techniques. In particular, we apply the successive convex approximations approach which relies on solving a series of convex problems that approximate the original (non-convex) one. The proposed solution resembles a power method for obtaining the dominant eigenvector of a matrix, which changes over iterations. Finally, the performance of the proposed detector is illustrated by means of computer simulations showing a great improvement over previously proposed detectors that do not fully exploit the temporal structure of the source."}],"place":"Prague, Czech Republic","date_updated":"2023-01-30T11:56:29Z"}