Theoretical analysis of word-level switching activity in the presence of glitching and correlation

This paper presents a novel analytical approach to compute the switching activity in digital circuits at the word level in the presence of glitching and correlation. The proposed approach makes use of signal statistics such as mean, variance, and autocorrelation, It is shown that the switching activity alpha(f) at the output node f of any arbitrary circuit in the presence of glitching and correlation is computed as {[}GRAPHICS] were {[}GRAPHICS] number of time slots in a cycle; time-slot autocorrelation coefficient; expected value of X; probability of the signal x being ``one.{''} The switching activity analysis of a signal at the word level is computed by summing the activities of all the individual bits constituting the signal. It is also shown that if the correlation coefficient of the higher order bits of a normally distributed signal x is p(xc), then the bit P-0 where the correlation begins and the correlation coefficient is related by p(xc) = erfc{(2(P0-1) - 1)/(root 2 sigma(x))} where erfc{x} complementary error function; variance of x. The proposed approach can estimate the switching activity in less than a second which is orders of magnitude faster than simulation based approaches, Simulation results show that the errors using the proposed approach are about 6.1% on an average and that the approach is well suited even for highly correlated speech and music signals.