Monte Carlo simulation applies to a wide range of estimation problems, but converges rather slowly in general. Variance reduction techniques can lower the estimation error, sometimes by a large factor, but rarely change the convergence rate of the estimation error. This error usually decreases as the inverse square root of the computational effort, as dictated by the central limit theorem. In t...

this paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...

State Sstimation over Fading Channels: Outage and Diversity Effects Kimmo Kansanen Department of Electronic and Telecommunications, Norwegian University of Science and Technology (NTNU), Norway Uncoded (analog) transmission of a scalar first-order Gauss-Markov process over fading channels is considered. This model is applicable in real-time applications and for settings such as wireless sensor ...

PREFACE 1.0 INTRODUCTION 2.0 BASIC CONCEPTS 2. I ECHO SIGNAL SINGLE TARGET 2.2 ECHO SIGNAL MULTIPLE TARGETS 2.3 CORRELATION 2.4 TIME AVERAGING 3.0 ABUNDANCE ESTIMATION 3.1 THICK SCATTERING LAYER 3.2 ENVELOPE SAMPLING 3.3 ENVELOPE INTEGRATION 3.4 THIN SCATTERING LAYER 3.5 VARIANCE ERROR THICK SCATTERING LAYER 3.6 VARIANCE ERROR THIN SCATTERING LAYER 4.0 SUMMARY 5.0 CONCLUSION APPENDIX A DISTRIBU...

Differenced estimators of variance bypass the estimation of regression function and thus are simple to calculate. However, there exist two problems: most differenced estimators do not achieve the asymptotic optimal rate for the mean square error; for finite samples the estimation bias is also important and not further considered. In this paper, we estimate the variance as the intercept in a lin...

This paper discusses the estimation of autocorrelation function ACF of fractional Gaussian noise fGn with long-range dependence LRD . A variance bound of ACF estimation of one block of fGn with LRD for a given value of the Hurst parameter H is given. The present bound provides a guideline to require the block size to guarantee that the variance of ACF estimation of one block of fGn with LRD for...

Recent empirical studies show that the estimated Markowitz mean-variance portfolios oftentimes perform rather poorly when there are more than several assets in the investment universe. In this article, we argue that such disappointing performance can be largely attributed to the estimation error incurred in sample mean-variance portfolios, and therefore could be improved by utilizing more effic...