9783846504109 - a subspace approach for speech signal modelling and classification: theory and algorithm de tan, alan w.c. (9 resultados)
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Taschenbuch. Condición: Neu. A Subspace Approach For Speech Signal Modelling And Classification | Theory and Algorithm | Alan W. C. Tan | Taschenbuch | 128 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846504109 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück…, mail[at]preigu[dot]de | Anbieter: preigu.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The subspace approach in speech signal analysis is commonly associated with the deployment of the singular value decomposition (SVD), or equivalently the eigendecomposition, to reveal useful subspace information about the signal of…interest. The general premise that information in speech signals is almost completely contained in a lower dimensional subspace of the measurement space underscores their principal role in detecting the desired signal subspace. These ideas, which have been vigorously researched for speech enhancement problems, inspire the notion of a signal subspace model. Signal subspace modelling, as developed in this thesis, generally relates to the representation of the speech signal in terms of the signal subspace information. The signal model is composed of a set of subspace trajectories, and these trajectories jointly characterize the subspace information of the signal under consideration. Relying on an important result on noisy measurement matrices, the notion of robustness in subspace classification is also established to facilitate the formulation of robust distortion measures. 128 pp. Englisch.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tan Alan W.C.Dr Alan Tan received the B.Eng. (Hons) degree in Electrical Engineering from University of Malaya, Kuala Lumpur, in 1999 on the Shell scholarship, and the M.EngSc. and Ph.D. degrees from Mu…ltimedia University, Selangor, .
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Condición: New. PRINT ON DEMAND pp. 128.
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The subspace approach in speech signal analysis is commonly associated with the deployment of the singular value decomposition (SVD), or equivalently the eigendecomposition, to reveal useful subspace information about the signal of inte…rest. The general premise that information in speech signals is almost completely contained in a lower dimensional subspace of the measurement space underscores their principal role in detecting the desired signal subspace. These ideas, which have been vigorously researched for speech enhancement problems, inspire the notion of a signal subspace model. Signal subspace modelling, as developed in this thesis, generally relates to the representation of the speech signal in terms of the signal subspace information. The signal model is composed of a set of subspace trajectories, and these trajectories jointly characterize the subspace information of the signal under consideration. Relying on an important result on noisy measurement matrices, the notion of robustness in subspace classification is also established to facilitate the formulation of robust distortion measures.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The subspace approach in speech signal analysis is commonly associated with the deployment of the singular value decomposition (SVD), or equivalently the eigendecomposition, to reveal useful subspace information about the signal of inter…est. The general premise that information in speech signals is almost completely contained in a lower dimensional subspace of the measurement space underscores their principal role in detecting the desired signal subspace. These ideas, which have been vigorously researched for speech enhancement problems, inspire the notion of a signal subspace model. Signal subspace modelling, as developed in this thesis, generally relates to the representation of the speech signal in terms of the signal subspace information. The signal model is composed of a set of subspace trajectories, and these trajectories jointly characterize the subspace information of the signal under consideration. Relying on an important result on noisy measurement matrices, the notion of robustness in subspace classification is also established to facilitate the formulation of robust distortion measures.
