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

ISBN 10: 3031196406 / ISBN 13: 9783031196409

Published by Springer Nature B.V., 2023

About this Item

New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Seller Inventory # L0-9783031196409

Bibliographic Details

• Title: Machine Learning Support for Fault Diagnosis of System-on-Chip
• Publisher: Springer Nature B.V.
• Publication Date: 2023
• Language: English
• ISBN 10: 3031196406
• ISBN 13: 9783031196409
• Binding: PAP
• Condition: New
• Weight: 465 grams

About this title

Synopsis

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.