A general framework for the least squares approximation of symmetric de nite pencils subject to generalized eigenvalues constraints is developed in this paper This approach can be adapted to di erent applications including the inverse eigenvalue problem The idea is based on the observation that a natural parameterization for the set of symmetric de nite pencils with the same generalized eigenva...

Modeling of yarn and fiber properties has been a popular topic in the field of textile engineering in recent decades. The common method for fitting models has been to use classical regression analysis, based on the assumptions of data crispness and deterministic relations among variables. However, in modeling practical systems such as cotton spinning, the above assumptions may not hold true. Pr...

This paper presents a new approach for the reduction of high order discrete time Interval systems based on least squares method and Time moments matching technique. The proposed method is computationally simple and overcomes some of the limitations and drawbacks of the existing methods. A numerical example illustrates the proposed algorithm.

We constraint on computer the best linear unbiased generalized statistics of random field for the best linear unbiased generalized statistics of an unknown constant mean of random field and derive the numerical generalized least-squares estimator of an unknown constant mean of random field. We derive the third constraint of spatial statistics and show that the classic generalized least-squares ...

This paper considers the problem of pricing options with early-exercise features whose payoff depends on several sources of uncertainty. We propose a stochastic grid method for estimating the upper and lower bound values of high-dimensional American options. The method is a hybrid of the least squares method of Longstaff and Schwartz (2001) [22], the stochastic mesh method of Broadie and Glasse...

In this work, the parameters of fuzzy linear regression based on the least squares approach is computed by ST-decomposition method. This method is not an iterative technique, however, it is a powerful method for nonsingular coefficient matrices. Numerical examples are at the end of this paper to illustrate the performance of the new method.

The paper presents the application of Least Squares moment matching method about a general point „a‟ for the reduction of high order Interval systems. A heuristic criteria have been employed for selecting the linear shift point „a‟ based upon the harmonic mean of real parts of the poles of four high order fixed systems obtained by Kharitonov‟s Theorem. The denominator polynomials are obtained b...

In this paper, a sensitivity analysis is carried out for the problem of simultaneous estimation of induction motor’s state and parameters. This is done using separable least squares formulation. It comes out that even in the presence of persistent excitations, the above problem is very sensitive to noises and/or uncertainties especially for one of the four possibly identifiable combinations of ...