Antonio Kolossa (27 results)

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  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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  • Language: English

    Published by Springer 2018-06-06, 2018

    3319812432 / 9783319812434

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  • Language: English

    Published by Springer, 2018

    3319812432 / 9783319812434

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  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

    • Hardcover

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  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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    Condition: New. pp. 127.

  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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  • Language: English

    Published by Springer, 2018

    3319812432 / 9783319812434

    • Softcover

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    Condition: New. pp. 127.

  • Language: English

    Published by Birkhäuser, 2018

    3319812432 / 9783319812434

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    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules.The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field.

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    Language: English

    Published by Springer, 2018

    3319812432 / 9783319812434

    • Softcover

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    Taschenbuch. Condition: Neu. Computational Modeling of Neural Activities for Statistical Inference | Antonio Kolossa | Taschenbuch | xxiv | Englisch | 2018 | Springer | EAN 9783319812434 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Language: English

    Published by Springer, 2018

    3319812432 / 9783319812434

    • Softcover

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    Paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Language: English

    Published by Palgrave Macmillan, 2016

    3319322842 / 9783319322841

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    Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This authored monograph supplies empirical evidence for the Bayesian brain hypothesis by modeling event-related potentials (ERP) of the human electroencephalogram (EEG) during successive trials in cognitive tasks. The employed observer models are useful to compute probability distributions over observable events and hidden states, depending on which are present in the respective tasks. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules. The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field.

  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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  • Language: English

    Published by Springer, 2018

    3319812432 / 9783319812434

    • Softcover
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  • Language: English

    Published by Springer International Publishing Mai 2018, 2018

    3319812432 / 9783319812434

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules.The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field. 152 pp. Englisch.

  • Language: English

    Published by Springer International Publishing Mai 2016, 2016

    3319322842 / 9783319322841

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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules.The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field. 152 pp. Englisch.

  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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    Condition: New. Print on Demand pp. 127.

  • Language: English

    Published by Springer, 2016

    3319322842 / 9783319322841

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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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    Condition: New. PRINT ON DEMAND pp. 127.

  • Language: English

    Published by Springer International Publishing, 2018

    3319812432 / 9783319812434

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides empirical evidence for the Bayesian brain hypothesis Presents observer models which are useful to compute probability distributions over observable events and hidden states Helps the reader to better understand the neural codin.

  • Language: English

    Published by Springer International Publishing, 2016

    3319322842 / 9783319322841

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    Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides empirical evidence for the Bayesian brain hypothesis Presents observer models which are useful to compute probability distributions over observable events and hidden states Helps the reader to better understand the neural codin.

  • Language: English

    Published by Springer, 2018

    3319812432 / 9783319812434

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    Condition: New. Print on Demand pp. 127.

  • Language: English

    Published by Springer, 2018

    3319812432 / 9783319812434

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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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    Condition: New. PRINT ON DEMAND pp. 127.

  • Language: English

    Published by Palgrave Macmillan, 2016

    3319322842 / 9783319322841

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    Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules.The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field.

  • Language: English

    Published by Springer, Palgrave Macmillan Mai 2018, 2018

    3319812432 / 9783319812434

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This authored monograph supplies empirical evidence for the Bayesian brain hypothesis by modeling event-related potentials (ERP) of the human electroencephalogram (EEG) during successive trials in cognitive tasks. The employed observer models are useful to compute probability distributions over observable events and hidden states, depending on which are present in the respective tasks. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules. The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 152 pp. Englisch.

  • Language: English

    Published by Springer, Palgrave Macmillan Mai 2016, 2016

    3319322842 / 9783319322841

    • Hardcover
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    Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This authored monograph supplies empirical evidence for the Bayesian brain hypothesis by modeling event-related potentials (ERP) of the human electroencephalogram (EEG) during successive trials in cognitive tasks. The employed observer models are useful to compute probability distributions over observable events and hidden states, depending on which are present in the respective tasks. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules. The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 152 pp. Englisch.