Aliasing Probability for Single Input Linear Feedback Signature Registers

This paper discusses a novel approach for calculating the exact aliasing probability for linear feedback signature register, which tracks the states of a fictitious linear feedback signature register comprised of two identical linear feedback signature register, one driven by the output sequence of the fault free circuit under test and the other driven by the output sequence of the faulty circuit under test. By deriving the state probability distribution of Markov Chain corresponding to the fictitious linear feedback signature register, we can be able to calculate the exact aliasing probability for any test input vector length. Furthermore, we investigate the dynamic properties of aliasing probability for linear feedback signature register. The analyses in the paper indicate that the asymmetric error model will provide more detailed information in modeling, analyzing, and the exact calculation of aliasing probability. Finally, simulation results will be shown for demonstrating the effectiveness of the approach proposed in the paper.