Publication Details
Nonstandard Automatic Test Pattern Generation Based on Neural Network Theory
Zbořil František, doc. Ing., CSc. (DITS)
Neural Networks, Combinational Logic Circuits, Test Pattern Generation
The paper deals with an unusual application of the Hopfield neural network for
test pattern generation of combinational logic circuits. The neural subnets
generating signals satisfying the functions of some standard gates are derived
and their merging to the net representing complex circuit is presented. To
generate a test pattern, two identical nets are created, the fault is injected to
the arbitrary net and both nets outputs are combined together to check them for
inequality. The nets themselves look for their neuron outputs (signals of logical
gates) satisfying all signal combinations and thus find the input signals
detecting the fault being modelled. The method has been verified on examples of
logical circuits containing tens of gates. The results are presented.
@inproceedings{BUT191442,
author="Zdeněk {Kotásek} and František {Zbořil}",
title="Nonstandard Automatic Test Pattern Generation Based on Neural Network Theory",
booktitle="Proceedings of the ECI'98",
year="1998",
pages="75--80",
publisher="Slovak Academy of Science",
address="Herlany",
isbn="80-88786-94-0"
}