在MATLAB中将数据拟合到B样条曲线

问题描述

我正在尝试估计时序数据中矩阵形式的缺失值.列代表时间点，即现在，我想将矩阵的每一行拟合为B样条曲线，并使用它来估计缺失值.我可以使用MATLAB将数据拟合为普通样条曲线，但是我完全陷入尝试找出如何拟合数据以创建B样条曲线的问题.使用``曲线拟合工具箱''中的默认bspline函数，可以将结矢量设置为时间点的矢量，但是无法设置控制点(即行的元素).
任何帮助将非常感激.

I am trying to estimate missing values in time-series data which is in the form of a matrix. The columns represent the time points,i.e. Now, I want to fit each row of the matrix to a B-Spline, and use it to estimate the missing values. I could fit the data to a normal spline using MATLAB, but I am completely stuck at trying to figure out how to fit the data to create a B-Spline. Using the default bspline function in the Curve Fitting Toolbox lets me set the knot vector to the vector of time points, but I cannot set the control points, i.e. the elements of the row.
Any help would be much appreciated.

添加示例

时间序列数据中的行如下所示:

The time-series data has rows that look like this:

-0.11    0.1    0.01    0.06    0.04   -0.26    0.04    0.19   -0.22    -0.2    0.12    0.21    -0.26    -0.3    0.22    0.58    -0.36    0.13

我的结向量基本上是时间点，看起来像这样:

My knot vector is basically the time points, and it looks like this:

 0     7    14    21    28    35    42    49    56    63    70    77    84    91    98   105   112   119

基本上，我想将每一行与结向量一起使用以构造B样条.

Basically I want to use each row along with the knot vector to construct a B-Spline.

推荐答案

这些是什么?

1. 快速B样条类
2. N维B样条
3. B样条工具
4. splinefit

1. Fast B-Spline class
2. N-dimensional B-splines
3. B-Spline tools
4. splinefit

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