Taguchi methods provide a comprehensive methodology for quality improvement. The objective is based on a robust design and involves conducting experiments using orthogonal arrays and the estimation factor levels combination that optimizes a given performance measure, typically a Signal-to-Noise ratio. The problem is more complex in the case of multiple responses since the combinations of factor...

Transversal Recursive Least Squares (RLS) algorithms estimate filter coefficients which minimize the accumulated sum of the square of the error residuals termed the error power. In this paper the sensitivity of this error power to random perturbations about the optimum filter coefficients is investigated. Expressions are derived for the mean and variance of the deviation from the optimum error ...

The minimum shift design problem (MSD) is a scheduling problem that commonly arises in workforce management activities. Given a collection of shifts and workforce requirements, the problem consists in finding a minimum cardinality set of work shifts, and the number of workers to assign to each shift, in order to meet (or minimize the deviation from) prespecified staff requirements. This problem...

The Least Mean Square (LMS) algorithm, introduced by Widrow and Hoff in 1959 [12] is an adaptive algorithm, which uses a gradient-based method of steepest decent [10]. LMS algorithm uses the estimates of the gradient vector from the available data. LMS incorporates an iterative procedure that makes successive corrections to the weight vector in the direction of the negative of the gradient vect...

in this paper, we consider portfolio selection problem in which security returns are regarded as fuzzy variables rather than random variables. we first introduce a concept of absolute deviation for fuzzy variables and prove some useful properties, which imply that absolute deviation may be used to measure risk well. then we propose two mean-absolute deviation models by defining risk as abs...

Motivated by studies on the recurrent properties of animal and human mobility, we introduce a path-dependent random-walk model with long-range memory for which not only the mean-square displacement (MSD) but also the propagator can be obtained exactly in the asymptotic limit. The model consists of a random walker on a lattice, which, at a constant rate, stochastically relocates at a site occupi...

We examine the linear and nonlinear modes of a one-dimensional electrical lattice, where usual discrete Laplacian is replaced by fractional Laplacian. This induces long-range intersite coupling that, at long distances, decreases as power law. In regime, we compute both, spectrum plane waves mean square displacement (MSD) an initially localized excitation, in closed form terms regularized hyperg...

To ascertain the stability of the β-barrel structure of the FpvA transporter in water, we measured the root mean square deviation (RMSD) of the barrel backbone to the experimental structure during the 50 ns production simulations of apo-FpvA, FpvA/PVDI and FpvA/PVD G173 , after fitting to the barrel α carbons to remove rigid-body rotation and translation (Figure S1). The small average mean squa...