DocumentCode
2426666
Title
Neural network classification of photoemission spectra
Author
Frank, Steve
Author_Institution
Texas Instruments, Inc., Dallas, TX, USA
fYear
2002
fDate
2002
Firstpage
205
Lastpage
209
Abstract
While the relationship between photoemission spectra and defects in integrated circuits has been well documented, the routine use of photoemission spectroscopy has been hampered by the difficulty of classifying the spectrum in the presence of noise. This paper proposes a neural network solution to this problem.
Keywords
failure analysis; integrated circuit testing; neural nets; photoelectron spectra; defect detection; failure analysis; integrated circuit; neural network classification; noise; photoemission spectra; Failure analysis; Instruments; Integrated circuit interconnections; Integrated circuit noise; Neural networks; Neurons; Photoelectricity; Semiconductor device noise; Signal to noise ratio; Spectroscopy;
fLanguage
English
Publisher
ieee
Conference_Titel
Reliability Physics Symposium Proceedings, 2002. 40th Annual
Print_ISBN
0-7803-7352-9
Type
conf
DOI
10.1109/RELPHY.2002.996637
Filename
996637
Link To Document