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Books > Computing & IT > Applications of computing > Databases > Data mining
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Knowledge-Driven Board-Level Functional Fault Diagnosis (Hardcover, 1st ed. 2017)
Loot Price: R2,530
Discovery Miles 25 300
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Knowledge-Driven Board-Level Functional Fault Diagnosis (Hardcover, 1st ed. 2017)
Expected to ship within 12 - 17 working days
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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.
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