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Accurate CMOS bridge fault modeling with neural network-based VHDL saboteurs

Published: 04 November 2001 Publication History

Abstract

This paper presents a new bridge fault model that is based on a multiple layer feedforward neural network and implemented within the framework of a VHDL saboteur cell. Empirical evidence and experimental results show that it satisfies a prescribed set of bridge fault model criteria better than existing approaches. The new model computes exact bridged node voltages and propagation delay times with due attention to surrounding circuit elements. This is significant since, with the exception of full analog simulation, no other technique attempts to model the delay effects of bridge defects. Yet, compared to these analog simulations, the new approach is orders of magnitude faster and achieves reasonable accuracy; computing bridged node voltages with an average error near 0.006 volts and propagation delay times with an average error near 14 ps.

References

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Cited By

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  • (2003)A circuit level fault model for resistive bridgesACM Transactions on Design Automation of Electronic Systems10.1145/944027.9440368:4(546-559)Online publication date: 1-Oct-2003

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Information

Published In

cover image ACM Conferences
ICCAD '01: Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
November 2001
656 pages
ISBN:0780372492
  • Conference Chair:
  • Rolf Ernst

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IEEE Press

Publication History

Published: 04 November 2001

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Author Tags

  1. CMOS ICs
  2. VHDL
  3. bridge defects
  4. fault models
  5. fault simulation
  6. neural networks

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  • Article

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ICCAD01
Sponsor:
ICCAD01: International Conference on Computer Aided Design
November 4 - 8, 2001
California, San Jose

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Overall Acceptance Rate 457 of 1,762 submissions, 26%

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  • (2003)A circuit level fault model for resistive bridgesACM Transactions on Design Automation of Electronic Systems10.1145/944027.9440368:4(546-559)Online publication date: 1-Oct-2003

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