Fangming ye (26 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319402099 / 9783319402093

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  • Lingua: Inglese

    Editore: Springer, 2018

    3319820540 / 9783319820545

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 2016

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  • Lingua: Inglese

    Editore: Springer 2018-06, 2018

    3319820540 / 9783319820545

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319402099 / 9783319402093

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319402099 / 9783319402093

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  • Lingua: Inglese

    Editore: Springer International Publishing AG, CH, 2016

    3319402099 / 9783319402093

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    Hardback. Condizione: New. 1st ed. 2017. This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.Explains and applies optimized techniques from the machine-learning      domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing.Demonstrates techniques based on industrial data and feedback from an actual manufacturing line.Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319402099 / 9783319402093

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  • Lingua: Inglese

    Editore: Springer, 2018

    3319820540 / 9783319820545

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    Condizione: New. pp. 160.

  • Lingua: Inglese

    Editore: Springer, 2016

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Hardcover. Condizione: Brand New. 147 pages. 9.75x6.75x0.75 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2018

    3319820540 / 9783319820545

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    Taschenbuch. Condizione: Neu. Knowledge-Driven Board-Level Functional Fault Diagnosis | Fangming Ye (u. a.) | Taschenbuch | xiii | Englisch | 2018 | Springer | EAN 9783319820545 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Birkhäuser, 2018

    3319820540 / 9783319820545

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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 - This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.-Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing;-Demonstrates techniques based on industrial data and feedback from an actual manufacturing line;-Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319402099 / 9783319402093

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

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    Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.-Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing;-Demonstrates techniques based on industrial data and feedback from an actual manufacturing line;-Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319402099 / 9783319402093

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    Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.¿ Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing;¿ Demonstrates techniques based on industrial data and feedback from an actual manufacturing line;¿ Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development.

  • Lingua: Inglese

    Editore: Springer International Publishing AG, CH, 2016

    3319402099 / 9783319402093

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    Hardback. Condizione: New. 1st ed. 2017. This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.Explains and applies optimized techniques from the machine-learning      domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing.Demonstrates techniques based on industrial data and feedback from an actual manufacturing line.Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development.

  • Lingua: Inglese

    Editore: Springer, 2018

    3319820540 / 9783319820545

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

  • Lingua: Inglese

    Editore: Springer, 2018

    3319820540 / 9783319820545

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319402099 / 9783319402093

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  • Lingua: Inglese

    Editore: Springer International Publishing Jun 2018, 2018

    3319820540 / 9783319820545

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.-Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing;-Demonstrates techniques based on industrial data and feedback from an actual manufacturing line;-Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development. 164 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer International Publishing Aug 2016, 2016

    3319402099 / 9783319402093

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

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    Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.-Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing;-Demonstrates techniques based on industrial data and feedback from an actual manufacturing line;-Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development. 164 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, 2018

    3319820540 / 9783319820545

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    Condizione: New. Print on Demand pp. 160.

  • Lingua: Inglese

    Editore: Springer International Publishing, 2018

    3319820540 / 9783319820545

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturingDemonstrates techniques based on industrial data and feedback from an actual .

  • Lingua: Inglese

    Editore: Springer International Publishing, 2016

    3319402099 / 9783319402093

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    Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturingDemonstrates techniques based on industrial data and feedback from an actual .

  • Lingua: Inglese

    Editore: Springer, 2018

    3319820540 / 9783319820545

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    Condizione: New. PRINT ON DEMAND pp. 160.

  • Lingua: Inglese

    Editore: Springer, Springer Jun 2018, 2018

    3319820540 / 9783319820545

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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 -This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 164 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, Springer Aug 2016, 2016

    3319402099 / 9783319402093

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    Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 164 pp. Englisch.