Isbn: 9781475704525 - pattern recognition with fuzzy objective function algorithms (advanced applications in pattern recognition) (10 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2012

    1475704526 / 9781475704525

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    Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections

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    Condición: New. In English.

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    Editorial: Springer, 2012

    1475704526 / 9781475704525

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    EUR 158,90

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    Condición: New. pp. 276.

  • Idioma: Inglés

    Editorial: Springer, 2012

    1475704526 / 9781475704525

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 167,65

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    Cantidad disponible: 2 disponibles

    Paperback. Condición: Brand New. reprint edition. 272 pages. 8.98x5.98x0.71 inches. In Stock.

  • Idioma: Inglés

    Editorial: Springer, Humana, 2012

    1475704526 / 9781475704525

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

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    EUR 164,69

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    Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.

  • Idioma: Inglés

    Editorial: Springer, 2012

    1475704526 / 9781475704525

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    Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    EUR 94,25

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    Condición: new. Questo è un articolo print on demand.

  • Idioma: Inglés

    Editorial: Springer US Mai 2012, 2012

    1475704526 / 9781475704525

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

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    EUR 117,69

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph. 276 pp. Englisch.

  • Idioma: Inglés

    Editorial: Springer US, 2012

    1475704526 / 9781475704525

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 101,04

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question o.

  • Idioma: Inglés

    Editorial: Springer, 2012

    1475704526 / 9781475704525

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    EUR 163,59

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    Condición: New. Print on Demand pp. 276 23:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on White w/Gloss Lam.

  • Idioma: Inglés

    Editorial: Springer, 2012

    1475704526 / 9781475704525

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    EUR 165,82

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    Condición: New. PRINT ON DEMAND pp. 276.

  • Idioma: Inglés

    Editorial: Springer, Humana Mai 2012, 2012

    1475704526 / 9781475704525

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    EUR 117,69

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 276 pp. Englisch.