Result Details

Nonstandard Automatic Test Pattern Generation Based on Neural Network Theory

KOTÁSEK, Z.; ZBOŘIL, F. Nonstandard Automatic Test Pattern Generation Based on Neural Network Theory. Proceedings of the ECI'98. Herlany: Slovak Academy of Science, 1998. p. 75-80. ISBN: 80-88786-94-0.
Type
conference paper
Language
English
Authors
Kotásek Zdeněk, doc. Ing., CSc.
Zbořil František, doc. Ing., CSc.
Abstract

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.

Keywords

Neural Networks, Combinational Logic Circuits, Test Pattern Generation

Published
1998
Pages
75–80
Proceedings
Proceedings of the ECI'98
Conference
Electronic Computers & Informatics 98
ISBN
80-88786-94-0
Publisher
Slovak Academy of Science
Place
Herlany
BibTeX 
@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"
}
Projects
Methodology and tools for digital circuits testability analysis, GACR, Standardní projekty, GA102/98/1463, start: 1998-01-01, end: 2006-03-31, completed
Research groups
Intelligent Systems Research Group (RG INTSYS)
Supercomputing Technologies Research Group SC@FIT (RG SC@FIT)
Departments
Faculty of Information Technology (FIT)
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