We consider the problem of estimating, in the presence of model uncertainties, a random vector x that is observed through a linear transformation H and corrupted by additive noise. We first assume that both the covariance of x and the transformation H are not completely specified, and develop the linear estimator that minimizes the worst-case mean-squared error (MSE) across all possible covaria...

The spacecraft simulator robust control through H∞-based linear matrix inequality (LMI) and robust adaptive method is  implemented. The spacecraft attitude control subsystem simulator consists of  a  platform, an air-bearing and a set of four reaction wheels. This set up provides a free real-time three degree of freedom rotation. Spacecraft simulators are applied in upgrading and checking the c...

In this paper, we propose a new multi-rate state estimator for seeking control of hard disk drives, which has a proportional, integral, and discontinuous error feedback structure to improve robustness. Conventional state estimators do not have enough accuracy under the existence of external disturbances and model uncertainty. With the proposed estimator, the seeking control system of hard disk ...

For the discretization of integral fractional Laplacian $(-\Delta )^s$, $0 < s 1$, based on piecewise linear functions, we present and analyze a reliable weighted residual posteriori error estimator. In order to compensate for lack $L^2$-regularity in regime $3/4 this estimator includes as an additional weight power distance from mesh skeleton. We prove optimal convergence rates $h$-adaptive al...

1 The local Whittle (or Gaussian semiparametric) estimator of long range dependence , proposed by Künsch (1987) and analyzed by Robinson (1995a), has a relatively slow rate of convergence and a finite sample bias that can be large. In this paper, we generalize the local Whittle estimator to circumvent these problems. Instead of approximating the short-run component of the spectrum, ϕ(λ) by a co...

In this study, an optimization model is proposed to design a Global Supply Chain (GSC) for a medical device manufacturer under disruption in the presence of pre-existing competitors and price inelasticity of demand. Therefore, static competition between the distributors’ facilities to more efficiently gain a further share in market of Economic Cooperation Organization trade agreement (ECOTA) is...

Estimation of large covariance matrices has drawn considerable recent attention, and the theoretical focus so far has mainly been on developing a minimax theory over a fixed parameter space. In this paper, we consider adaptive covariance matrix estimation where the goal is to construct a single procedure which is minimax rate optimal simultaneously over each parameter space in a large collectio...

Abstract: The problem of estimating the centre of symmetry of an unknown periodic function observed in Gaussian white noise is considered. Using the penalized blockwise James-Stein method, a smoothing filter allowing to define the penalized profile likelihood is proposed. The estimator of the centre of symmetry is then the maximizer of this penalized profile likelihood. This estimator is shown ...

Consider a problem of predicting a response variable using a set of covariates in a linear regression model. If it is a priori known or suspected that a subset of the covariates do not significantly contribute to the overall fit of the model, a restricted model that excludes these covariates, may be sufficient. If, on the other hand, the subset provides useful information, shrinkage meth...

IQ imbalance is a serious RF front-end impairment and in this work, we study the issue of IQ imbalance correction using a combination of iterative and adaptive signal processing techniques. First, we propose an estimator based on EM algorithm for the case of a Bit Interleaved Coded modulation Iterative Detection (BICM-ID) receiver for burst mode communications. The resulting TURBO IQ Decorrelat...