Numerical analysis

Computes a smooth regularized solution of an ill-posed discrete linear inverse problem. in matlab

The following Matlab project contains the source code and Matlab examples used for computes a smooth regularized solution of an ill-posed discrete linear inverse problem. . This package computes a smooth regularized solution of an ill-posed linear inverse problem by a non-linear constraint minimization algorithm using the L-curve criterion.

Fits circles to 2d data using nonlinear least squares to minimise geometric error in matlab

The following Matlab project contains the source code and Matlab examples used for fits circles to 2d data using nonlinear least squares to minimise geometric error . Although a linear least squares fit of a circle to 2D data can be computed, this is not the solution which minimizes the distances from the points to the fitted circle (geometric error).

Distance matrix in matlab

The following Matlab project contains the source code and Matlab examples used for distance matrix. Returns the point-to-point distance between all pairs of points (similar to PDIST in the Statistics Toolbox, for those without it)   DMAT = DISTMAT(XY) Calculates the distance matrix using an automatic option DMAT = DISTMAT(XY,OPT) Uses the specified option to compute the distance matrix [DMAT,OPT] = DISTMAT(XY) Also returns the automatic option used by the function   Inputs: XY is an NxP matrix of coordinates for N points in P dimensions

Newton raphson in matlab

The following Matlab project contains the source code and Matlab examples used for newton raphson. This M-file calculates all the real roots of the given polynomial. It calls syn_division, a synthetic division function, and derivate, differentiation function.

This functions implements the algorithm of orthogonal least squares. it can be used to rank regresso in matlab

The following Matlab project contains the source code and Matlab examples used for this functions implements the algorithm of orthogonal least squares. it can be used to rank regresso . [x, ind] = OLS(A,b,r) gives the solution to the least squares problem using only the best r regressors chosen from the ones present in matrix A.

Biparabolic interpolation in matlab

The following Matlab project contains the source code and Matlab examples used for biparabolic interpolation. Code to interpolate surface values using a parabolic approximation in both X and Y directions. Parabola coefficients are further used to calculate approximated values of first and second partial derivatives at the requested node of interpolation.

A wrap of lsqnonlin using complex step differentiation to get jacobian in matlab

The following Matlab project contains the source code and Matlab examples used for a wrap of lsqnonlin using complex step differentiation to get jacobian . Complex step differentiation (CSD) is a superior numerical differentiation approach. Normally, it is more efficient and accurate than finite difference appraoch. This package provides a way to improve the MATLAB lsqnonlin function using the CSD.

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