Isbn: 9783846504109 - a subspace approach for speech signal modelling and classification: theory and algorithm (9 resultados)

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  • Idioma: Inglés

    Editorial: Editorial Academica Espanola, 2011

    3846504106 / 9783846504109

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    Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle

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    Condición: New. pp. 128.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2011

    3846504106 / 9783846504109

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    Librería: preigu, Osnabrück, Alemaniapreigu

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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.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2011

    3846504106 / 9783846504109

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    Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books

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    Condición: Usado - Como Nuevo

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    Cantidad disponible: 1 disponibles

    Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2011, 2011

    3846504106 / 9783846504109

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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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.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2011

    3846504106 / 9783846504109

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    Librería: moluna, Greven, Alemaniamoluna

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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 Multimedia University, Selangor, .

  • Idioma: Inglés

    Editorial: Editorial Academica Espanola, 2011

    3846504106 / 9783846504109

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    EUR 98,25

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    Condición: New. Print on Demand pp. 128 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

  • Idioma: Inglés

    Editorial: Editorial Academica Espanola, 2011

    3846504106 / 9783846504109

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    Condición: New. PRINT ON DEMAND pp. 128.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2011, 2011

    3846504106 / 9783846504109

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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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 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2011

    3846504106 / 9783846504109

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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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 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.