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Robustness of least-squares and subspace methods for blind channel identification/equalization algorithms with respect to channel undermodeling

Liavas Athanasios, Delmas, Fernand, Regalia, Phillip A., 1962-

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URIhttp://purl.tuc.gr/dl/dias/A35861DE-3D72-4F98-AB7C-08B54B679544-
Αναγνωριστικόhttp://faculty.cua.edu/regalia/regalia-perso_files/eusipco-98a.pdf-
Γλώσσαen-
Μέγεθος4 pagesen
ΤίτλοςRobustness of least-squares and subspace methods for blind channel identification/equalization algorithms with respect to channel undermodelingen
ΔημιουργόςLiavas Athanasiosen
ΔημιουργόςΛιαβας Αθανασιοςel
ΔημιουργόςDelmas, Fernanden
ΔημιουργόςRegalia, Phillip A., 1962-en
ΠερίληψηThe least-squares and the subspace methods are well known approaches for blind channel identification/equalization. When the order of the channel is known, the algorithms are able to identify the channel, under the so-called length and zero conditions. Furthermore, in the noiseless case, the channel can be perfectly equalized. Less is known about the performance of these algorithms in the cases in which the channel order is underestimated. We partition the true impulse response into the significant part and the tails. We show that the m-th order least-squares or subspace methods estimate an impulse response which is “close” to the m-th order significant part of the true impulse response. The closeness depends on the diversity of the m-th order significant part and the size of the “unmodeled” parten
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-09-
Ημερομηνία Δημοσίευσης1998-
Βιβλιογραφική ΑναφοράA. P. Liavas, P. A. Regalia and J-P. Delmas.(1998).Robustness of least-squares and subspace methods for blind channel identification/equalization algorithms with respect to channel undermodeling.Presented at European Signal Processing Conference.[online].Available:http://faculty.cua.edu/regalia/regalia-perso_files/eusipco-98a.pdfen

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