在matlab中拟合二维曲线
曲线拟合工具箱有一个名为 cftool 的工具箱函数,可让您将曲线拟合为一维数据。有二维数据的东西吗?
There's a toolbox function for the curve fitting toolbox called cftool that lets you fit curves to 1-d data. Is there anything for 2-d data?
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杰瑞提出了两个非常好的选择。不过,如果您想要更公式化的模型形式,还有其他选择。
当前版本中的曲线拟合工具箱允许您将曲面拟合到数据,而不仅仅是曲线。
或者使用 polyfitn 等工具拟合二维多项式模型。
或者,如果您心中有模型,则可以使用非线性回归。优化工具箱将帮助您,使用 lsqnonlin 或 lsqcurvefit,其中任何一个都可以拟合二维(或更高)模型。或者,如果您有统计工具箱,请尝试 nlinfit。
也许您可能需要一个适合径向基函数。
神经网络是另一种拟合数据的方法,因此请使用 神经网络工具箱
所以有很多方法根据您的兴趣、您对模型可能形式的了解、您拥有的工具箱或您可能选择下载的内容来对曲面进行建模。选择模型的一个非常重要的因素是模型的目标。你会用它做什么?它将如何使用?
Jerry suggested two very good choices. There are other options though, if you want a more formulaic form for the model.
The curvefitting toolbox, in the current version, allows you to fit surfaces to data, not just curves.
Or fit a 2-d polynomial model, using a tool like polyfitn.
Or you can use a nonlinear regression, if you have a model in mind. The optimization toolbox will help you there, with lsqnonlin or lsqcurvefit, either of which can fit 2-d (or higher) models. Or, if you have the stats toolbox, then try nlinfit.
Perhaps you might like a tool to fit Radial Basis Functions.
Neural nets are another way to fit data, so use the Neural Network Toolbox
So there are many ways to model surfaces, depending on your interests, your knowledge of a likely form for the model, what toolboxes you have or what you might choose to download. A very big factor in your model choice are your goals for the model. What will you do with it? How will it be used?
您似乎正在寻找 griddata。您可能还想查看 gridfit。
You seem to be looking for griddata. You might also want to look at gridfit.