High dimensional data are becoming more and more common in data analysis. This is especially true in fields that are related to spectrometric data, such as chemometrics. Due to development of more accurate spectrometers one can obtain spectra of thousands of data points. Such a high dimensional data are problematic in machine learning due to increased computational time and the curse of dimensi...

In this initial chapter we consider some of the basic methods used in the fitting of data by real and complex linear combinations of exponentials. We have selected the classes of methods that are most frequently used in many different fields: variable projections for solving this separable nonlinear least squares problem, derivatives and variants of Prony’s method, which rely on evenly sampled ...

We investigate different techniques for fitting Bézier curves to surfaces in context of high-order curvilinear mesh generation. Starting from distance-based least-squares fitting we develop an incremental algorithm, which incorporates approximations of stretch and bending energy. In the process, the algorithm reduces the energy weight in favor of accuracy, leading to an optimized set of samplin...

this paper used a general equilibrium model to evaluate the effects of adjustment polices. the model includes both demand and supply side equations. relationships concerning household and government income are also included in model. iterative three-stage least squares method is used-toestimatethe.model: then the mode/is used to simulate the effect of sevenaltemative policies on poverty and inc...

in this paper, an iterative method is proposed for solving matrix equation $sum_{j=1}^s a_jx_jb_j = e$. this method is based on the global least squares (gl-lsqr) method for solving the linear system of equations with the multiple right hand sides. for applying the gl-lsqr algorithm to solve the above matrix equation, a new linear operator, its adjoint and a new inner product are de ned. it is ...

The usual way of the implementation of on-line discrete Hilbert transformers is the design of linear phase finite impulse response (FIR) filters. Recently, a method has been published for the design of infinite impulse response (IIR) Hilbert transformers as well. The paper introduces a new method for the design of both FIR and IIR Hilbert transformers, based on a parameter estimation method for...

Matrix trace inequalities are finding increased use in many areas such as analysis, where they can be used to generalise several well known classical inequalities, and computational statistics, where they can be applied, for example, to data fitting problems. In this paper we give simple proofs of two useful matrix trace inequalities and provide applications to orthogonal regression and matrix ...