Least squares estimators are developed for the parameters in the autocorrelation function of a stationary process. Regularity conditions for consistency and asymptotic normality are given, and optimal weights are derived. It is shown how goodness of fit and model selection can be based on the distance between empirical and fitted autocorrelations. Examples of sums of Ornstein-Uhlenbeck type pro...

Collocated active and passive remote sensing measurements collected at U.S. Department of Energy Atmospheric Radiation Measurement Program sites enable simultaneous retrieval of cloud and precipitation properties and air motion. Previous studies indicate the parameters of a bimodal cloud particle size distribution can be effectively constrained using a combination of passive microwave radiomete...

For the problem that the traditional static positioning algorithms can not locate the mobile network node accurately, and the traditional Monte Carlo localization algorithm features low positioning accuracy and poor positioning accuracy due to the low sampling efficiency of the nodes, an improved Monte Carlo (Higher Monte Carlo, HMCL) localization algorithm is thereby proposed. The RSSI distanc...

We study multipath parameter estimation from orthogonal frequency division multiplex signals transmitted over doubly dispersive mobile radio channels. We are interested in cases where the transmission is long enough to suffer time selectivity, but short enough such that the time variation can be accurately modeled as depending only on per-tap linear phase variations due to Doppler effects. We t...

introduction : due to the importance of laser light penetration and propagation in biological tissues, many researchers have proposed several numerical methods such as monte carlo, finite element and green function methods. among them, the monte carlo method is an accurate method which can be applied for different tissues. however, because of its statistical nature, monte carlo simulation requi...