Programmatic Curve Fitting To programmatically fit a curve, follow the steps in this simple example: Load some data. load hahn1 Create a fit using the fit function, specifying the variables and a model type (in this case rat23 is the model type). f = fit(temp,thermex,"rat23") Plot yo...
y = [2.78331.45551.66662.43211.98821.78220.99990.32331.43210.9212]; 2.2. Matlab自带拟合工具 curve fitting 2.3. 加载数据 路径:Matlab-APP-Curve fitting 为x data 和y data 加载数据,由原先输入x、y可以得到。 2.4. 选择拟合曲线类型 选择拟合类型fit type 和拟合的方式,通过fit options 限定拟合的起始点参数...
Find the Best Fitting Parameters Start from a random positive set of parametersx0, and havefminsearchfind the parameters that minimize the objective function. x0 = rand(2,1); bestx = fminsearch(fun,x0) bestx =2×140.6877 0.4984
function f=my(x,t)f=5./(x(1)*sqrt(t)+x(2));采纳哦 亲 私聊
Fit Polynomial to Trigonometric Function Generate 10 points equally spaced along a sine curve in the interval[0,4*pi]. x = linspace(0,4*pi,10); y = sin(x); Usepolyfitto fit a 7th-degree polynomial to the points. p = polyfit(x,y,7); ...
其次,当您使用Curve Fitting Tool进行拟合时,可以通过设置FittedFunction属性来指定输出函数。例如,如果您已经定义了一个名为myFunc的自定义输出函数,您可以在拟合过程中将其设置为FittedFunction属性。 最后,您可以使用fplot函数来绘制拟合曲线和原始数据点。通过指定拟合函数作为fplot函数的第一个参数,您可以可视化您的输出...
6 使用lsqcurvefit 实现非线性拟合的基本步骤1. 给定已知的数据 (x, y) 以及x y 之间满足的函数关系 y = f(x)1.1 确定 y = f(x) 中的待定参数 param = [r, ym]1.2 定义拟合函数 y = f(x) ： function y = curvefun (param, x)1.3 给定参数的初值param0：调用lsqcurvefit 求解2. 计算拟合...
%handle=@(arglist)anonymous_function%其中handle为调用匿名函数时使用的名字。%arglist为匿名函数的输入参数,可以是一个,也可以是多个,用逗号分隔。%anonymous_function为匿名函数的表达式。%举个小例子%z=@(x,y)x^2+y^2;%z(1,2)%%ans=5%fplot函数可用于画出匿名一元函数的图形。%fplot(f,xinterval)将...
I would like to fit a curve to a set of data (I know the function is periodic). The problem is, all the fittings I tried are unable to reproduced the periodicity of the function. Is there any way to use the curve fitting toolbox to fit a periodic function data set using only 1 ...
function F = myfun(x, xdata) F = x(1)*exp(x(2)*xdata) + x(3) - ydata; end 然后在命令行中进行拟合: matlab xdata = [1, 2, 3, 4, 5]; ydata = [2.718, 7.389, 20.085, 54.598, 148.413]; x0 = [1, 1, 1]; % 初始猜测值 x = lsqcurvefit(@myfun, x0, xdata, ydata)...