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portada Machine Learning Support for Fault Diagnosis of System-On-Chip
Type
Physical Book
Publisher
Author
Language
English
Pages
316
Format
Hardcover
Dimensions
23.4 x 15.6 x 1.9 cm
Weight
0.64 kg.
ISBN13
9783031196386
Categories

Machine Learning Support for Fault Diagnosis of System-On-Chip

Girard, Patrick ; Blanton, Shawn ; Wang, Li-C (Author) · Springer · Hardcover

Machine Learning Support for Fault Diagnosis of System-On-Chip - Girard, Patrick ; Blanton, Shawn ; Wang, Li-C

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Synopsis "Machine Learning Support for Fault Diagnosis of System-On-Chip"

This book provides a state-of-the-art guide to Machine Learning (ML)-based techniques that have been shown to be highly efficient for diagnosis of failures in electronic circuits and systems. The methods discussed can be used for volume diagnosis after manufacturing or for diagnosis of customer returns. Readers will be enabled to deal with huge amount of insightful test data that cannot be exploited otherwise in an efficient, timely manner. After some background on fault diagnosis and machine learning, the authors explain and apply optimized techniques from the ML domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing. These techniques can be used for failure isolation in logic or analog circuits, board-level fault diagnosis, or even wafer-level failure cluster identification. Evaluation metrics as well as industrial case studies are used to emphasize the usefulness and benefits of using ML-based diagnosis techniques.

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