Abstract

This work applies the paradigm of the machine learning to the identification of type and position of short-and open-circuit defects along a three-dimensional daisy-chain signal channel in presence of through silicon vias. A suitable artificial neural network is designed, trained, and used for this task. This contribution discusses the advantages and limitations of this approach quantifying the differences among the real and estimated positions of the defects.

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