Fernando gaxiola (14 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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    Condizione: As New. Unread book in perfect condition.

  • Lingua: Inglese

    Editore: Springer 2016-06-09, 2016

    3319340867 / 9783319340869

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    Da: Chiron Media, Wallingford, Regno UnitoChiron Media

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    Paperback. Condizione: New.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Springer 6/9/2016, 2016

    3319340867 / 9783319340869

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    Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores

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    Paperback or Softback. Condizione: New. New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks. Book.

  • Lingua: Inglese

    Editore: Springer-Verlag New York Inc, 2016

    3319340867 / 9783319340869

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    EUR 76,65

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    Paperback. Condizione: Brand New. 112 pages. 9.00x6.00x0.50 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for ô=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.

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    Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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    Taschenbuch. Condizione: Neu. New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks | Fernando Gaxiola (u. a.) | Taschenbuch | SpringerBriefs in Applied Sciences and Technology | ix | Englisch | 2016 | Springer | EAN 9783319340869 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319340867 / 9783319340869

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

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

  • Lingua: Inglese

    Editore: Springer International Publishing Jun 2016, 2016

    3319340867 / 9783319340869

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 53,49

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for ô=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error. 112 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer International Publishing, 2016

    3319340867 / 9783319340869

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    Da: moluna, Greven, Germaniamoluna

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Proposes a neural network learning method with type-2 fuzzy weight adjustment Presents a mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weightsPresents simulation results and a comparati.

  • Lingua: Inglese

    Editore: Springer, Springer Jun 2016, 2016

    3319340867 / 9783319340869

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 112 pp. Englisch.