Title :
Neural network classification of photoemission spectra
Author_Institution :
Texas Instruments, Inc., Dallas, TX, USA
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;
Conference_Titel :
Reliability Physics Symposium Proceedings, 2002. 40th Annual
Print_ISBN :
0-7803-7352-9
DOI :
10.1109/RELPHY.2002.996637
