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
Click the top to follow for more content. Feel free to share. For details, contact Teacher Wang: 13521993969 Fitting of 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 … Read more
This note covers the course listened to: Teacher Guo Yanfu on Bilibili (original version on YouTube) “12 Statistics, 13 Regression and Interpolation” Criticism and corrections are welcome (1) Statistics1. Descriptive Statistics(1) Central Tendency1) Functions — Calculate xxx①mean()–Mean ②median()–Median ③mode()–Mode ④prctile()–Percentile ⑤max()–Maximum ⑥min()–Minimumeg. X = [1 3 5 5 5 5 7 9 9 9 10 … Read more