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Aliasing probabilities for feedback signature compression of test data

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1 Author(s)
Robinson, J.P. ; Dept. of Electr. & Comput. Eng., Iowa Univ. Iowa City, IA, USA

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

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Computers, IEEE Transactions on  (Volume:40 ,  Issue: 7 )