Neural Network Simulation Environments (23 results)

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  • Language: English

    Published by Springer, 1994

    0792394151 / 9780792394150

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  • Language: English

    Published by Springer, 1994

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  • Language: English

    Published by Springer, 2012

    146136180X / 9781461361800

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  • Language: English

    Published by Springer, 1994

    0792394151 / 9780792394150

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  • Language: English

    Published by Springer, 2012

    146136180X / 9781461361800

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    Condition: New. pp. 280.

  • Language: English

    Published by Springer, 1994

    0792394151 / 9780792394150

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  • Language: English

    Published by Springer, 2012

    146136180X / 9781461361800

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    Taschenbuch. Condition: Neu. Neural Network Simulation Environments | Josef Skrzypek | Taschenbuch | The Springer International Series in Engineering and Computer Science | xxiii | Englisch | 2012 | Springer | EAN 9781461361800 | 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 US, 1994

    0792394151 / 9780792394150

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    Condition: Sehr gut. Zustand: Sehr gut | Seiten: 280 | Sprache: Englisch | Produktart: Bücher | Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data. Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.

  • Language: English

    Published by Springer, Springer, 2012

    146136180X / 9781461361800

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data. Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.

  • Language: English

    Published by Springer, 1994

    0792394151 / 9780792394150

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  • Language: English

    Published by Springer, 2012

    146136180X / 9781461361800

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  • Language: English

    Published by Springer, 2012

    146136180X / 9781461361800

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  • Language: English

    Published by Springer US Sep 2012, 2012

    146136180X / 9781461361800

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data. Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject. 280 pp. Englisch.

  • Language: English

    Published by Springer US Feb 1994, 1994

    0792394151 / 9780792394150

    • Hardcover
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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 -Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data. Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject. 280 pp. Englisch.

  • Language: English

    Published by Springer US, 2012

    146136180X / 9781461361800

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software .

  • Language: English

    Published by Springer US, 1994

    0792394151 / 9780792394150

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    Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software .

  • Language: English

    Published by Springer, 1994

    0792394151 / 9780792394150

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    Condition: New. Print on Demand pp. 280 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

  • Language: English

    Published by Springer, Springer Feb 1994, 1994

    0792394151 / 9780792394150

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    Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Neural Network Simulation Environments describes some of the best examples of neural simulation environments.All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data.Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 280 pp. Englisch.

  • Language: English

    Published by Springer, Springer Sep 2012, 2012

    146136180X / 9781461361800

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Neural Network Simulation Environments describes some of the best examples of neural simulation environments.All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data.Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 280 pp. Englisch.

  • Language: English

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    146136180X / 9781461361800

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    Condition: New. Print on Demand pp. 280 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

  • Language: English

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    146136180X / 9781461361800

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    Condition: New. PRINT ON DEMAND pp. 280.

  • Language: English

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    0792394151 / 9780792394150

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  • Language: English

    Published by Humana, 1994

    0792394151 / 9780792394150

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    Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data. Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.