Advertisement

Conclusions

Chapter
  • 437 Downloads

Abstract

This book has presented a set of intelligent diagnostic methods to reduce the dependence of board-level diagnosis on time-consuming and ineffective human effort. Multiple machine learning and statistical methods have been studied and adapted for diagnosis. Substantial improvement has been achieved over currently deployed diagnostic software. These solutions are not limited to a particular product; they are generic and can therefore be applied to various products. Although the goal of this book was to advance board-level diagnosis, the core techniques described in this book can also be leveraged for larger electronic systems.

Keywords

Board-level Data-mining Fault diagnosis Functional failures Machine learning Knowledge-driven 

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Huawei TechnologiesSanta ClaraUSA
  2. 2.Department of Electrical and Computer EngineeringDuke UniversityDurhamUSA

Personalised recommendations