Polynomial Fitting clear x=1:1:10;y=-0.9*x.^2+10*x+20+rand(1,10).*5; % Generate test data plot(x,y,‘o’) % Plot and mark the original data points p=polyfit(x,y,2) p = 1×3 -0.7630 8.5343 25.9050 xi=1:0.5:10; yi=polyval(p,xi); % Calculate the fitting result hold onplot(xi,yi); % Draw the fitting result graph hold off clear x = linspace(0,4*pi,10)'; y = sin(x); p = polyfit(x,y,7); x1 = linspace(0,4*pi); y1 … Read more
Previously, the derivation of the least squares method was introduced, which is widely used in function differentiation. When using it, existing tools can be directly utilized to solve (for example, using A\b in MATLAB to solve for x). However, sometimes it is necessary to handle constraint problems, so it is essential to master the constrained … Read more
Source: This article is from Wang Fuchang’s blog on ScienceNet, Author: Wang Fuchang. Fitting measurement data has wide applications in scientific research and engineering. Below are several commonly used fitting methods and how to implement them in the MATLAB environment. In MATLAB, there are commands for fitting such as polyfit, lsqcurvefit, nlinfit, and the curve … Read more