Data driven neural-based measurement discrimination for IC parametric faults diagnosis

Abstract

Describes experimental results obtained with the use of data driven neural-based system for statistical IC fault diagnosis. Measurement discrimination is established through a reduction method involving data pre-processing in a fashion consistent with a specific definition of parametric faults. The effects of this preprocessing are examined in the context of a realistic IC parametric fault diagnostic problem.<>