An Adaptive Nonlinear Least-Squares Algorithm

An Efficient Algorithm for the Separable Nonlinear Least Squares Problem

The nonlinear least squares problem miny,z‖A(y)z + b(y)‖, where A(y) is a full-rank (N + `)× N matrix, y ∈ Rn, z ∈ RN and b(y) ∈ RN+` with ` ≥ n, can be solved by first solving a reduced problem miny‖ f (y)‖ to find the optimal value y∗ of y, and then solving the resulting linear least squares problem minz‖A(y∗)z + b(y∗)‖ to find the optimal value z∗ of z. We have previously justified the use o...

Nonlinear Partial Least Squares: An Overview

In many areas of research and industrial situations, including many data analytic problems in chemistry, a strong nonlinear relation between different sets of data may exist. While linear models may be a good simple approximation to these problems, when nonlinearity is severe they often perform unacceptably. The nonlinear partial least squares (PLS) method was developed in the area of chemical ...

Nonlinear Least-squares Estimation

The paper uses empirical process techniques to study the asymptotics of the least-squares estimator for the fitting of a nonlinear regression function. By combining and extending ideas of Wu and Van de Geer, it establishes new consistency and central limit theorems that hold under only second moment assumptions on the errors. An application to a delicate example of Wu’s illustrates the use of t...

An Estimation Of Seasonal GDP Gap In Iran: Application Of Adaptive Least Squares Methods

A Nonlinear Adaptive Beamforming Algorithm Based on Least Squares Support Vector Regression

To overcome the performance degradation in the presence of steering vector mismatches, strict restrictions on the number of available snapshots, and numerous interferences, a novel beamforming approach based on nonlinear least-square support vector regression machine (LS-SVR) is derived in this paper. In this approach, the conventional linearly constrained minimum variance cost function used by...