Unsupervised learning for signal mapping in dynamic photon emission

S. Chef*, S. Jacquir, K. Sanchez, P. Perdu, S. Binczak, C. L. Gan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Dynamic photon emission is an efficient tool for timing analysis of various areas. However, advances in transistors integration bring more complex test patterns and more objects to investigate. As a consequence, understanding the analyzed area and finding nodes of interest can be difficult. In this paper, a method for drawing synthesis of the various signals met inside an area is reported. It is based on unsupervised learning tool for dimension reduction and clustering. The process is applied to real data to show its efficiency and its quality is evaluated.

Original languageEnglish
Pages (from-to)1564-1568
Number of pages5
JournalMicroelectronics Reliability
Volume55
Issue number9-10
DOIs
Publication statusPublished - Aug 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Ltd.

ASJC Scopus Subject Areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Condensed Matter Physics
  • Safety, Risk, Reliability and Quality
  • Surfaces, Coatings and Films
  • Electrical and Electronic Engineering

Keywords

  • Circuit analysis
  • Defect localization
  • Photon emission
  • Signal mapping
  • Signal processing
  • Unsupervised learning

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