Numerical integration is fundamental in multiple Monte Carlo rendering problems. We present a sample reweighting scheme, including underlying theory, and analysis of numerical performance for the an unknown one-dimensional function. Our method simple to implement builds upon insight link weights function reconstruction process during integration. provide proof that our solution unbiased cases c...

abstract: this paper is the first study on the impact of ambient temperature on the electrical characteristics and high frequency performances of double gate armchair graphene nanoribbon field effect transistor (gnrfet). the results illustrate that the gnrfet under high temperature (ht-gnrfet) has the highest cut-off frequency, lowest sub-threshold swing, lowest intrinsic delay and power delay ...

Let {Xn, n >= 1} be a strictly stationary sequence of negatively associated random variables, with common continuous and bounded distribution function F. In this paper, we consider the estimation of the two-dimensional distribution function of (X1,Xk+1) based on histogram type estimators as well as the estimation of the covariance function of the limit empirical process induced by the se...

This work describes a parallel implementation of Very Fast Simulated Reannealing (VFSR), an advanced simulated annealing method for optimization of non-linear, multi-dimensional functions with large numbers of local minima. Parallel VFSR speed-ups on a CM-2 connection machine are reported for eight functions: De Jong's test suite, a 10-D parabolic function , and two multi-modal, highly non-line...

Geophysical measurements such as seismic datasets contain valuable information that originate from areas of interest in the subsurface; these reflections are however inevitably contaminated by other events created waves reverberating overburden. Multi-Dimensional Deconvolution (MDD) is a powerful technique used at various stages processing sequence to create ideal deprived overburden effects. W...

Convex regression is concerned with computing the best fit of a convex function to a data set of n observations in which the independent variable is (possibly) multi–dimensional. Such regression problems arise in operations research, economics, and other disciplines in which imposing a convexity constraint on the regression function is natural. This paper studies a least squares estimator that ...