A penalty/least-squares method for optimal control problems for ®rst-order elliptic systems is considered wherein the constraint equations are enforced via penalization. The convergence, as the penalty parameter tends to zero, of the solution to the penalized optimal control problem to that of the unpenalized one is demonstrated as is the convergence of a gradient method for determining solutio...

soil conservation service (scs) adjusted the kostiakovs infiltration model by adding a constant coefficient, for improvement of estimation. the improved model has three constant parameters, which are difficult to calculate. so scs has taken the third constant parameter as equal to 0.65-0.7 cm to simplify the estimation. this parameter varies in different soil and often outranges the scs estimat...

In this paper a numerical method based on least-squares approximation is proposed for elliptic interface problems in two dimensions, where the interface is smooth. The underlying method is spectral element method. In the least-squares formulation a functional is minimized as defined in (4.1). The jump in the solution and its normal derivative across the interface are enforced (in an appropriate...

Estimation theory has been developed over centuries. There are several approaches to utilizing this theory; in this chapter, these approaches are classified into three types. Type I includes the oldest two methods, the least squares (LS) and moment methods; both of these methods are non-optimal estimators. The least squares method was introduced by Carl Friedrich Gauss. Least squares problems f...

For fast detection of inorganic phosphorus fractions and their phosphorus contents in soil, a method employing near-infrared spectroscopy (NIRS) combined with partial least squares (PLS) and least squares support vector machine (LS-SVM) was proposed. Fifty soil samples for each of iron phosphate, magnesium phosphate, calcium phosphate and aluminum phosphate, with application rates of phosphate ...

In previous work we introduced a construction to produce biorthogonal multiresolutions from given subdivisions. The approach involved estimating the solution to a least squares problem by means of a number of smaller least squares approximations on local portions of the data. In this work we use a result by Dahlquist, et. al. on the method of averages to make observational comparisons between t...

Pixel unmixing is commonly performed by employing a least squared (LS) error criterion, making it sensitive to outliers. As an alternative, the least median of squares (LMedS) method is proposed. Not only is it extremely robust, but it is efficient and straightforward both to implement and use.

We propose a goal-oriented, local a posteriori error estimator for H(div) least-squares (LS) finite element methods. Our main interest is to develop an a posteriori error estimator for the flux approximation in a preassigned region of interest D ⊂ Ω. The estimator is obtained from the LS functional by scaling residuals with proper weight coefficients. The weight coefficients are given in terms ...

In this paper a novel hybrid algorithm for harmonics estimation in power systems is proposed. The estimation of the harmonic components is a nonlinear problem due to the nonlinearity of phase of sinusoids in distorted waveforms. Most researchers implemented nonlinear methods to extract the harmonic parameters. However, nonlinear methods for amplitude estimation increase time of convergence. Hen...