No abstract

The authors discuss aliasing errors in signature analysis registers for self-testing networks and review analytical results. The results show that when p, the probability that an error will occur at a network output, is close to 1/2, there is a bound of the aliasing error. The analysis uses a graph to represent the probability of transition, the Markov process, and z-transforms to analyze the behavior of the signature analysis register. For very small p (p-0) and very large p (p-1), the aliasing error solution for primitive polynomials is a series of terms (1-)' in magnitude (where n is the number of random patterns being applied to the network or the length of the network output sequence). As compared with nonprimitive polynomials, whose solution is n(1-)n or n2(1-)p, in general primitive polynomials are much better with respectto aliasing. Simulation results are shown for aliasing errors for these polynomials, which give insight as to how aliasing occurs.

No abstract

No abstract

No abstract