Performance and Improvement of MCS Selection with Channel Quality Estimation Errors for HSDPA

The throughput performance of modulation and coding schemes （MCS） selection with channel quality estimation errors （CQEE） is analyzed for high-speed downlink packet access （HSDPA）. To reduce the loss of throughput caused by CQEE, the robust MCS selection method and adaptive MCS switching scheme are proposed. In addition, automatic repeat request （ARQ） scheme is used to improve the block error rate （BLER） performance. Simulation results show that the proposed methods decrease the throughput loss resulted from CQEE efficiently and BLER performance gets better with ARQ scheme.

Sensitivity to Estimation Errors in Mean-variance Models

Abstract In order to give a complex and accurate description about the sensitivity of efficient portfolios to changes in asset's expected returns, variances and covariances, the joint effect of estimation errors in means, variances and covariances on the efficient portfolio's weights is investigated in this paper. It is proved that the efficient portfolio's composition is a Lipschitz continuous, differentiable mapping of these parameters under suitable conditions. The change rate of the efficient portfolio's weights with respect to variations about risk-return estimations is derived by estimating the Lipschitz constant. Our general quantitative results show that the efficient portfolio's weights are normally not so sensitive to estimation errors about means and variances. Moreover, we point out those extreme cases which might cause stability problems and how to avoid them in practice. Preliminary numerical results are also provided as an illustration to our theoretical results.

Existence and numerical approximation of a solution to frictional contact problem for electro-elastic materials

In this paper,a frictional contact problem between an electro-elastic body and an electrically conductive foundation is studied.The contact is modeled by normal compliance with finite penetration and a version of Coulomb’s law of dry friction in which the coefficient of friction depends on the slip.In addition,the effects of the electrical conductivity of the foundation are taken into account.This model leads to a coupled system of the quasi-variational inequality of the elliptic type for the displacement and the nonlinear variational equation for the electric potential.The existence of a weak solution is proved by using an abstract result for elliptic variational inequalities and a fixed point argument.Then,a finite element approximation of the problem is presented.Under some regularity conditions,an optimal order error estimate of the approximate solution is derived.Finally,a successive iteration technique is used to solve the problem numerically and a convergence result is established.

A Priori Error Analysis for NCVEM Discretization of Elliptic Optimal Control Problem

In this paper, we propose the nonconforming virtual element method (NCVEM) discretization for the pointwise control constraint optimal control problem governed by elliptic equations. Based on the NCVEM approximation of state equation and the variational discretization of control variables, we construct a virtual element discrete scheme. For the state, adjoint state and control variable, we obtain the corresponding prior estimate in H1 and L2 norms. Finally, some numerical experiments are carried out to support the theoretical results.

Efficient error estimation in quantum key distribution

In a quantum key distribution（QKD） system, the error rate needs to be estimated for determining the joint probability distribution between legitimate parties, and for improving the performance of key reconciliation. We propose an efficient error estimation scheme for QKD, which is called parity comparison method（PCM）. In the proposed method, the parity of a group of sifted keys is practically analysed to estimate the quantum bit error rate instead of using the traditional key sampling. From the simulation results, the proposed method evidently improves the accuracy and decreases revealed information in most realistic application situations.

An Online Model Correction Method Based on an Inverse Problem:Part I—Model Error Estimation by Iteration

Errors inevitably exist in numerical weather prediction （NWP） due to imperfect numeric and physical parameterizations. To eliminate these errors, by considering NWP as an inverse problem, an unknown term in the prediction equations can be estimated inversely by using the past data, which are presumed to represent the imperfection of the NWP model （model error, denoted as ME）. In this first paper of a two-part series, an iteration method for obtaining the MEs in past intervals is presented, and the results from testing its convergence in idealized experiments are reported. Moreover, two batches of iteration tests were applied in the global forecast system of the Global and Regional Assimilation and Prediction System （GRAPES-GFS） for July-August 2009 and January-February 2010. The datasets associated with the initial conditions and sea surface temperature （SST） were both based on NCEP （National Centers for Environmental Prediction） FNL （final） data. The results showed that 6th h forecast errors were reduced to 10% of their original value after a 20-step iteration. Then, off-line forecast error corrections were estimated linearly based on the 2-month mean MEs and compared with forecast errors. The estimated error corrections agreed well with the forecast errors, but the linear growth rate of the estimation was steeper than the forecast error. The advantage of this iteration method is that the MEs can provide the foundation for online correction. A larger proportion of the forecast errors can be expected to be canceled out by properly introducing the model error correction into GRAPES-GFS.

THE SUPERIORITY OF EMPIRICAL BAYES ESTIMATION OF PARAMETERS IN PARTITIONED NORMAL LINEAR MODEL

In this article,the empirical Bayes（EB）estimators are constructed for the estimable functions of the parameters in partitioned normal linear model.The superiorities of the EB estimators over ordinary least-squares（LS）estimator are investigated under mean square error matrix（MSEM）criterion.

Enriched goal-oriented error estimation for fracture problems solved by continuum-based shell extended finite element method

An enriched goal-oriented error estimation method with extended degrees of freedom is developed to estimate the error in the continuum-based shell extended finite element method. It leads to high quality local error bounds in three-dimensional fracture mechanics simulation which involves enrichments to solve the singularity in crack tip. This enriched goal-oriented error estimation gives a chance to evaluate this continuum- based shell extended finite element method simulation. With comparisons of reliability to the stress intensity factor calculation in stretching and bending, the accuracy of the continuum-based shell extended finite element method simulation is evaluated, and the reason of error is discussed.

Cooperative interception with fast multiple model adaptive estimation

For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang-bang evasive maneuver with a random switching time.Combined Fast multiple model adaptive estimation(Fast MMAE)algorithm,the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration.Introduced the detection error model related to the line-of-sight(LOS)separation angle of two interceptors,an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance.Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion,Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately.The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation.

Application of an Error Statistics Estimation Method to the PSAS Forecast Error Covariance Model

In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Pfiysical-space Statistical Analysis System （PSAS） height-wind forecast error covariance model. This method consists of two components： the first component computes the error statistics by using the National Meteorological Center （NMC） method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation （MLE） with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office （GMAO）, NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.

Using self-location to calibrate the errors of observer positions for source localization

The uncertainty of observers＇ positions can lead to significantly degrading in source localization accuracy. This pa-per proposes a method of using self-location for calibrating the positions of observer stations in source localization to reduce the errors of the observer positions and improve the accuracy of the source localization. The relative distance measurements of the two coordinative observers are used for the linear minimum mean square error （LMMSE） estimator. The results of computer si-mulations prove the feasibility and effectiveness of the proposed method. With the general estimation errors of observers＇ positions, the MSE of the source localization with self-location calibration, which is significantly lower than that without self-location calibra-tion, is approximating to the Cramer-Rao lower bound （CRLB）.

Array-error estimation method for multi-channel SAR systems in azimuth

For multi-channel synthetic aperture radar（SAR） systems, since the minimum antenna area constraint is eliminated,wide swath and high resolution SAR image can be achieved.However, the unavoidable array errors, consisting of channel gainphase mismatch and position uncertainty, significantly degrade the performance of such systems. An iteration-free method is proposed to simultaneously estimate position and gain-phase errors.In our research, the steering vectors corresponding to a pair of Doppler bins within the same range bin are studied in terms of their rotational relationships. The method is based on the fact that the rotational matrix only depends on the position errors and the frequency spacing between the paired Doppler bins but is independent of gain-phase error. Upon combining the projection matrices corresponding to the paired Doppler bins, the position errors are directly obtained in terms of extracting the rotational matrix in a least squares framework. The proposed method, when used in conjunction with the self-calibration algorithm, performs stably as well as has less computational load, compared with the conventional methods. Simulations reveal that the proposed method behaves better than the conventional methods even when the signal-to-noise ratio（SNR） is low.

Channel Error Estimation Methods Comparison under Different Conditions for Multichannel HRWS SAR Systems

Multichannel synthetic aperture radar (SAR) in azimuth can resolve the contradiction between high resolution and wide swath faced with traditional SAR imaging. However, channel errors will degrade the performance of imaging. This paper compares the performances of four channel error estimation algorithms under different clutter distributions and SNR conditions. Further, explanations are given for performance differences of the four algorithms, which provide evidence for method selection in engineering applications.

ERROR ESTIMATION OF INTERPOLATION ON PORE STRUCTURE ANALYSIS

In this paper we computed the data of pore structure with Lagrange interpolation method, analyzed the convergence of the method and deduced the corresponding error estimation formula.

A POSTERIORI ERROR ESTIMATION OF THE NEW MIXED ELEMENT SCHEMES FOR SECOND ORDER ELLIPTIC PROBLEM ON ANISOTROPIC MESHES

This paper presents a posteriori residual error estimator for the new mixed el-ement scheme for second order elliptic problem on anisotropic meshes. The reliability and efficiency of our estimator are established without any regularity assumption on the mesh.

Goal-oriented error estimation applied to direct solution of steady-state analysis with frequency-domain finite element method

Based on the concept of the constitutive relation error along with the residuals of both the origin and the dual problems, a goal-oriented error estimation method with extended degrees of freedom is developed. It leads to the high quality locM error bounds in the problem of the direct-solution steady-state dynamic analysis with a frequency-domain finite element, which involves the enrichments with plural variable basis functions. The solution of the steady-state dynamic procedure calculates the harmonic response directly in terms of the physical degrees of freedom in the model, which uses the mass, damping, and stiffness matrices of the system. A three-dimensional finite element example is carried out to illustrate the computational procedures.

Systematic error real-time registration based onmodified input estimation

In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.

Image enhancement via MMSE estimation of Gaussian scale mixture with Maxwell density in AWGN

In optical techniques,noise signal is a classical problem in medical image processing.Recently,there has been considerable interest in using the wavelet transform with Bayesian estimation as a powerful tool for recovering image from noisy data.In wavelet domain,if Bayesian estimator is used for denoising problem,the solution requires a prior knowledge about the distribution of wavelet coeffcients.Indeed,wavelet coeffcients might be better modeled by super Gaussian density.The super Gaussian density can be generated by Gaussian scale mixture(GSM).So,we present new minimum mean square error(MMSE)estimator for spherically-contoured GSM with Maxwell distribution in additive white Gaussian noise(AWGN).We compare our proposed method to current state-of-the-art method applied on standard test image and we quantify achieved performance improvement.

Improving precision of field inventory estimation of aboveground biomass through an alternative view on plot biomass

We contrast a new continuous approach(CA)for estimating plot-level above-ground biomass(AGB)in forest inventories with the current approach of estimating AGB exclusively from the tree-level AGB predicted for each tree in a plot,henceforth called DA(discrete approach).With the CA,the AGB in a forest is modelled as a continuous surface and the AGB estimate for a fixed-area plot is computed as the integral of the AGB surface taken over the plot area.Hence with the CA,the portion of the biomass of in-plot trees that extends across the plot perimeter is ignored while the biomass from trees outside of the plot reaching inside the plot is added.We use a sampling simulation with data from a fully mapped two hectare area to illustrate that important differences in plot-level AGB estimates can emerge.Ideally CA-based estimates of mean AGB should be less variable than those derived from the DA.If realized,this difference translates to a higher precision from field sampling,or a lower required sample size.In our case study with a target precision of 5%(i.e.relative standard error of the estimated mean AGB),the CA required a 27.1%lower sample size for small plots of 100 m2 and a 10.4%lower sample size for larger plots of 1700 m2.We examined sampling induced errors only and did not yet consider model errors.We discuss practical issues in implementing the CA in field inventories and the potential in applications that model biomass with remote sensing data.The CA is a variation on a plot design for above-ground forest biomass;as such it can be applied in combination with any forest inventory sampling design.

Error Estimations, Error Computations, and Convergence Rates in FEM for BVPs

This paper presents derivation of a priori error estimates and convergence rates of finite element processes for boundary value problems (BVPs) described by self adjoint, non-self adjoint, and nonlinear differential operators. A posteriori error estimates are discussed in context with local approximations in higher order scalar product spaces. A posteriori error computational framework (without the knowledge of theoretical solution) is presented for all BVPs regardless of the method of approximation employed in constructing the integral form. This enables computations of local errors as well as the global errors in the computed finite element solutions. The two most significant and essential aspects of the research presented in this paper that enable all of the features described above are: 1) ensuring variational consistency of the integral form(s) resulting from the methods of approximation for self adjoint, non-self adjoint, and nonlinear differential operators and 2) choosing local approximations for the elements of a discretization in a subspace of a higher order scalar product space that is minimally conforming, hence ensuring desired global differentiability of the approximations over the discretizations. It is shown that when the theoretical solution of a BVP is analytic, the a priori error estimate (in the asymptotic range, discussed in a later section of the paper) is independent of the method of approximation or the nature of the differential operator provided the resulting integral form is variationally consistent. Thus, the finite element processes utilizing integral forms based on different methods of approximation but resulting in VC integral forms result in the same a priori error estimate and convergence rate. It is shown that a variationally consistent (VC) integral form has best approximation property in some norm, conversely an integral form with best approximation property in some norm is variationally consistent. That is best approximation property of the integral form and the VC of the integral form is equivalent, one cannot exist without the other, hence can be used interchangeably. Dimensional model problems consisting of diffusion equation, convection-diffusion equation, and Burgers equation described by self adjoint, non-self adjoint, and nonlinear differential operators are considered to present extensive numerical studies using Galerkin method with weak form (GM/WF) and least squares process (LSP) to determine computed convergence rates of various error norms and present comparisons with the theoretical convergence rates.