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Knowledge-Driven Board-Level Functional Fault Diagnosis
Ye, Fangming; Zhang, Zhaobo; Chakrabarty, Krishnendu
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Description for Knowledge-Driven Board-Level Functional Fault Diagnosis
Hardback. Num Pages: 160 pages, 10 black & white illustrations, 65 colour illustrations, 64 colour tables, biography. BIC Classification: TJFC; UNF. Category: (G) General (US: Trade). Dimension: 235 x 155 x 11. Weight in Grams: 415.
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 ... Read more
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 ... Read more
Product Details
Format
Hardback
Publication date
2016
Publisher
Springer International Publishing AG Switzerland
Number of pages
160
Condition
New
Number of Pages
147
Place of Publication
Cham, Switzerland
ISBN
9783319402093
SKU
V9783319402093
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Ye, Fangming; Zhang, Zhaobo; Chakrabarty, Krishnendu
Fangming Ye is a Staff Engineer at Huawei Technologies, with particular research interests in machine learning, data mining, resilient system design, and diagnosis system for board-level faults. Zhaobo Zhang is a Staff Engineer at Huawei Technologies, specializing in Data analysis and machine learning, Network reliability, Application design, Flow standardization, diagnosis automation, and memory test. ... Read more
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