This Article 
 Bibliographic References 
 Add to: 
Aliasing Probabilities for Feedback Signature Compression of Test Data
July 1991 (vol. 40 no. 7)
pp. 867-873

A computationally efficient Markov state space model is developed for determining the aliasing probability of a linear feedback shift register when used for test data reduction. The model studied can be used to test data errors which have a constant of probability of error, correlated or repeated use errors, or time varying error probability. Based on a number of simulations of various error models and feedback polynomials it appears that a primitive polynomial, with about half its terms nonzero, has the best dynamic performance in most cases.

[1] R. A. Frohwerk, "Signature analysis: A new digital field service method,"Hewlett-Packard J., pp. 2-8, May 1977.
[2] E. J. McCluskey, "Built-in self test techniques,"IEEE Design Test Mag., pp. 21-28, Apr. 1985.
[3] J. E. Smith, "Measures of the effectiveness of fault signature analysis,"IEEE Trans. Comput., vol. C-29, no. 6, pp. 510-514, June 1980.
[4] T. W. Williamset al., "Aliasing errors in signature analysis registers,"IEEE Design Test Mag., pp. 39-45, Apr. 1987.
[5] S. W. Golomb,Shift Register Sequences, rev. ed. Laguna Hills, CA: Aegean Park Press, 1982.
[6] A. Avizienis, "A study of the effectiveness of fault-detection codes for binary arithmetic," Jet Propulsion Lab. Tech. Rep. 32-711, Sept. 1965.

Index Terms:
feedback signature compression; Markov state space model; aliasing probability; linear feedback shift register; data reduction; error models; feedback polynomials; logic testing; Markov processes; shift registers.
J.P. Robinson, "Aliasing Probabilities for Feedback Signature Compression of Test Data," IEEE Transactions on Computers, vol. 40, no. 7, pp. 867-873, July 1991, doi:10.1109/12.83625
Usage of this product signifies your acceptance of the Terms of Use.