A technique .of initialization for the primitive forecast equations is presented. The method consists of a marching prediction scheme performed in such a manner that the large-scale solution remains approximately steady, and high-frequency modes created in the adjustment process are damped selectively by time differencing with the Eulerbackward method. The scheme places no restriction on the wi...

We consider properties of revisions to mean square optimal concurrent estimates of unobserved components, e.g., seasonal adjustments or trends, obtained by ARIMA model-based signal extraction methods like those used by SEATS. Concurrent estimates, i.e., the estimate for the most recent month (or quarter), are updated whenever future observations become available, and the difference between the ...

in order to decrease the risks associated with the management of urban watersheds, the use of proper methods is an essential task to estimate the runoff with a high degree of confidence. time of concentration is one of factors that impacts on peak discharge and runoff volume. the objective of this study is to select the best method among the empirical formulas for estimating the time of concent...

In Wireless Sensor Networks (WSNs), localization algorithms could be range-based or range-free. The Approximate Point in Triangle (APIT) is a range-free approach. We propose modification of the APIT algorithm and refer as modified-APIT. We select suitable triangles with appropriate distance between anchors to reduce PIT test errors (edge effect and non-uniform placement of neighbours) in APIT a...

We describe a scalable experimental protocol for estimating the average error of individual quantum computational gates. This protocol consists of interleaving random Clifford gates between the gate of interest and provides an estimate as well as theoretical bounds for the average error of the gate under test, so long as the average noise variation over all Clifford gates is small. This techniq...

Acoustic feature transformation is widely used to reduce dimensionality and improve speech recognition performance. In this letter we focus on dimensionality reduction methods that minimize the average classification error. Unfortunately, minimization of the average classification error may cause considerable overlaps between distributions of some classes. To mitigate risks of considerable over...

In this paper, we propose a modeling approach that captures the dependence of the power dissipation of a combinational logic circuit on its input/output signal switching statistics. The resulting power macromodel, consisting of a single four-dimensional (4-D) table, can be used to estimate the power consumed in the circuit for any given input/output signal statistics. Given a low-level (typical...