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Knowledge-Driven Board-Level Functional Fault Diagnosis (en Inglés)
Krishnendu Chakrabarty
(Autor)
·
Zhaobo Zhang
(Autor)
·
Fangming Ye
(Autor)
·
Springer
· Tapa Blanda
Knowledge-Driven Board-Level Functional Fault Diagnosis (en Inglés) - Ye, Fangming ; Zhang, Zhaobo ; Chakrabarty, Krishnendu
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Origen: Estados Unidos
(Costos de importación incluídos en el precio)
Se enviará desde nuestra bodega entre el
Miércoles 17 de Julio y el
Miércoles 24 de Julio.
Lo recibirás en cualquier lugar de Internacional entre 1 y 3 días hábiles luego del envío.
Reseña del libro "Knowledge-Driven Board-Level Functional Fault Diagnosis (en Inglés)"
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.