You might also like

More about Knowledge-Driven Board-Level Functional Fault Diagnosis

• Book details
• Synopsis
• Trending among others

You get 217 loyalty points

Book synopsis

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.

Book details

• Full title: Knowledge-Driven Board-Level Functional Fault Diagnosis
• Author: FANGMING YE
• Language: English
• Binding: Paperback
• Number of pages: 147
• EAN: 9783319820545
• ISBN: 9783319820545
• ID: 19755637
• Publisher: Springer International Publishing AG
• Weight: 454 g
• Dimensions: 235 × 155 × 10 mm
• Date of publishing: 14. June 2018

Trending among others

---

---

---