Matlab直线拟合和平面拟合VIP专享VIP免费

利用Matlab 实现直线和平面的拟合 2011-04-14 10:45:43| 分类： 算法思想 |举报|字号 订阅 直线和平面拟合是很常用的两个算法，原理非常简单。但如果matlab 不太熟的话，写起来也不是那么容易。搜了很久才找到这两个代码，保存之，免得日后麻烦。 1、直线拟合的matlab 代码 % Fitting a best-fit line to data, both noisy and non-noisy x = rand(1,10); n = rand(size(x)); % Noise y = 2*x + 3; % x and y satisfy y = 2*x + 3 yn = y + n; % x and yn roughly satisfy yn = 2*x + 3 due to the noise % Determine coefficients for non-noisy line y=m1*x+b1 Xcolv = x(:); % Make X a column vector Ycolv = y(:); % Make Y a column vector Const = ones(size(Xcolv)); % Vector of ones for constant term Coeffs = [Xcolv Const]\Ycolv; % Find the coefficients m1 = Coeffs(1); b1 = Coeffs(2); % To fit another function to this data, simply change the first % matrix on the line defining Coeffs % For example, this code would fit a quadratic % y = Coeffs(1)*x^2+Coeffs(2)*x+Coeffs(3) % Coeffs = [Xcolv.^2 Xcolv Const]\Ycolv; % Note the .^ before the exponent of the first term % Plot the original points and the fitted curve figure plot(x,y,'ro') hold on x2 = 0:0.01:1; y2 = m1*x2+b1; % Evaluate fitted curve at many points plot(x2, y2, 'g-') title(sprintf('Non-noisy data: y=%f*x+%f',m1,b1)) % Determine coefficients for noisy line yn=m2*x+b2 Xcolv = x(:); % Make X a column vector Yncolv = yn(:); % Make Yn a column vector Const = ones(size(Xcolv)); % Vector of ones for constant term NoisyCoeffs = [Xcolv Const]\Yncolv; % Find the coefficients m2 = NoisyCoeffs(1); b2 = NoisyCoeffs(2); % Plot the original points and the fitted curve figure plot(x,yn,'ro') hold on x2 = 0:0.01:1; yn2 = m2*x2+b2; plot(x2, yn2, 'g-') title(sprintf('Noisy data: y=%f*x+%f',m2,b2)) 2、平面...