this paper studies the sequential sampling scheme, as a solution to the problem of aliasing, where the sampling interval is restricted to a minimum allowable value d t. in the sequential sampling, the signal is sampled at intervals of d t, d t+ dt , d t+2 dt , d t+3 dt , ...; where dt < d t and may be selected as desirable. the sequential sampling is, however, analyzed and it is proven that, wh...

In this paper, we propose new sequential estimation methods based on inclusion principle. The main idea is to reformulate the estimation problems as constructing sequential random intervals and use confidence sequences to control the associated coverage probabilities. In contrast to existing asymptotic sequential methods, our estimation procedures rigorously guarantee the pre-specified levels o...

We present a sequential noise compensation method based on the sequential Kullback proximal algorithm, which uses the Kullback-Leibler divergence as a regularization function for the maximum likelihood estimation. The method is implemented as filters. In contrast to sequential noise compensation method based on the sequential EM algorithm, the convergence rate of the method and estimation error...

We describe an approach to estimate the average power dissipation in sequential logic circuits under user-specified input sequences or programs. This approach will aid the design of programmable controllers or processors, by enabling the estimation of the power dissipated when the controller or processor is running specific application programs. Current approaches to sequential circuit power es...

Quantiles are convenient measures of the entire range of values of simulation outputs. However, unlike the mean and standard deviation, the observations have to be stored since calculation of quantiles requires several passes through the data. Thus, quantile estimation(QE) requires a large amount of computer storage and computation time. Several approaches for estimating quantiles in RS(regener...