Partial least square (PLS) analysis is the most favourite tool in chemometrics to develop calibration models. PLS technique allows us decipher even complex systems by analysing all variables instead of looking at them one a time. not only capture maximum variation associated with predictor (i.e. spectra) and predicted concentration) but also maximises correlation between them. The present artic...

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...

The moving least-square technique is used to construct shape function in the Element Free Galerkin Method at present, but sometimes the algebra equations system obtained from the moving least-square approximation is ill-conditioned and the shape function needs large quantity of inverse operation. In this paper, the weighted orthogonal functions are used as basis ones, the application in the cal...