- nonlinear least squares algorithm
- нелинейный алгоритм уравнивания методом наименьших квадратов
Англо-русский словарь промышленной и научной лексики. 2014.
nonlinear least squares algorithm
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Least-squares spectral analysis — (LSSA) is a method of estimating a frequency spectrum, based on a least squares fit of sinusoids to data samples, similar to Fourier analysis. [cite book | title = Variable Stars As Essential Astrophysical Tools | author = Cafer Ibanoglu |… … Wikipedia
Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… … Wikipedia
Total least squares — The bivariate (Deming regression) case of Total Least Squares. The red lines show the error in both x and y. This is different from the traditional least squares method which measures error parallel to the y axis. The case shown, with deviations… … Wikipedia
Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… … Wikipedia
Non-linear iterative partial least squares — In statistics, non linear iterative partial least squares (NIPALS) is an algorithm for computing the first few components in a principal component or partial least squares analysis. For very high dimensional datasets, such as those generated in… … Wikipedia
Nonlinear regression — See Michaelis Menten kinetics for details In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or… … Wikipedia
Nonlinear dimensionality reduction — High dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lies on an embedded non linear manifold within… … Wikipedia
Nonlinear programming — In mathematics, nonlinear programming (NLP) is the process of solving a system of equalities and inequalities, collectively termed constraints, over a set of unknown real variables, along with an objective function to be maximized or minimized,… … Wikipedia
Levenberg–Marquardt algorithm — In mathematics and computing, the Levenberg–Marquardt algorithm (LMA)[1] provides a numerical solution to the problem of minimizing a function, generally nonlinear, over a space of parameters of the function. These minimization problems arise… … Wikipedia
Gauss–Newton algorithm — The Gauss–Newton algorithm is a method used to solve non linear least squares problems. It can be seen as a modification of Newton s method for finding a minimum of a function. Unlike Newton s method, the Gauss–Newton algorithm can only be used… … Wikipedia
Digital image correlation — and Tracking (DIC/DDIT) is an optical method that employs tracking image registration techniques for accurate 2D and 3D measurements of changes in images. This is often used to measure deformation (engineering), displacement, and strain, but it… … Wikipedia
