Piecewise linear least square fit

Fit experimental data with linear piecewise continuos function with given x-axis break points.
Updated Fri, 22 Mar 2013 17:08:19 +0000

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Generates 1-D look-up table (LUT) optimal (least-square sense with continuity constraint) y-axis points from experimental (x,y) data given a vector of x-axis break points.

Note that x-axis break points should be chosen such that every bin has enough data points for correct estimation.

Please see lsq_lut_piecewise_test.m for an example with (synthetic) experimental data points.

No toolbox required.

% LSQ_LUT_PIECEWISE Piecewise linear interpolation for 1-D interpolation (table lookup)
% YI = lsq_lut_piecewise( x, y, XI ) obtain optimal (least-square sense)
% vector to be used with linear interpolation routine.
% The target is finding Y given X the minimization of function
% f = |y-interp1(XI,YI,x)|^2
% x measured data vector
% y measured data vector
% XI break points of 1-D table
% YI interpolation points of 1-D table
% y = interp1(XI,YI,x)

Cite As

Guido Albertin (2024). Piecewise linear least square fit (https://www.mathworks.com/matlabcentral/fileexchange/40913-piecewise-linear-least-square-fit), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2006b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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