This paper considers the problem of sampling frequency offset (SFO) estimation for orthogonal frequency division multiplexing (OFDM) based digital radio mondiale (DRM) systems. In this study, the mean square error (MSE) expression for conventional SFO estimators is derived and their low-complexity variants are reported. The theoretical MSE analysis for different algorithms are validated by Mont...

The problem of forming images that are optimal with respect to a Mean Square Error (MSE) criterion, based on nite data, is considered. First, it is shown that the MSE criterion is consistent with the general goal of classifying images, in that decreasing the MSE guarantees a decrease in the probability of misclassifying an image. The problem of choosing sampling locations for image formation th...

This paper presents a Comparative Study of NLMS (Normalized Least Mean Square) and ENSS (Error Normalized Step Size) LMS (Least Mean Square) algorithms. For this System Identification (An Adaptive Filter Application) is considered. Three performances Criterion are utilized in this study: Minimum Mean Square error (MSE), Convergence Speed, the Algorithm Execution Time. The Step Size Parameter (μ...

This paper proposes an affine projection algorithm (APA) with variable projection order using the mean-square error (MSE) criterion. The proposed algorithm determines the projection order at every iteration to use it in the update equation of the proposed APA. The MSE criterion is employed to decide the projection order reasonably. Moreover, this algorithm checks the steady-state condition to c...

The ratio-type estimators have been introduced for estimating the mean and total population, but in recent years based on the ratio methods several estimators for population variance have been proposed. In this paper two families of estimators have been suggested and their approximation mean square error (MSE) have been developed. In addition, the efficiency of these variance estimators are com...

We present an algorithm for low rank approximation of matrices where only some of the entries in the matrix are taken into consideration. This algorithm appears in recent literature under different names, where it is described as an EM based algorithm that maximizes the likelihood for the missing entries without any relation for the mean square error minimization. When the algorithm is minimize...

An almost unbiased estimator using known value of some population parameter(s) is proposed. Under simple random sampling without replacement (SRSWOR) scheme the expressions for bias and mean square error (MSE) are derived. Numerical illustrations are given.

In this paper, we consider the steady state mean square error (MSE) analysis for 2-D LMS adaptive filtering algorithm in which the filter’s weights are updated along both vertical and horizontal directions as a doubly-indexed dynamical system. The MSE analysis is conducted using the well-known independence assumption. First we show that computation of the weight-error covariance matrix for doub...

Accurately estimating software effort is probably the biggest challenge facing software developers. Estimates done at the proposal stage has high degree of inaccuracy, where requirements for the scope are not defined to the lowest details, but as the project progresses and requirements are elaborated, accuracy and confidence on estimate increases. It is important to choose the right software ef...