Coefficient Matrix Of Cubic Spline Interpolation.

In summary, the conversation discusses deriving the coefficient matrix for a parabolically terminated cubic spline and the necessary equations and conditions for solving the system. The conversation also touches on how the first and last rows of the matrix and vector change when the end conditions are ##-a_1 + a_2 = 0## and ##-a_{n-1} + a_n = 0##.
  • #1
SherlockOhms
310
0

Homework Statement


I'm trying to derive the coefficient matrix (a) of a parabolically terminated cubic spline. This is the matrix of coefficients ##a_i \rightarrow a_n## where n is the number of data points provided.

With this matrix you can find all the other coefficients (b and c) that define the spline using: $$b_i = \frac{y_i}{h_i} - a_i h_i$$ where ##y_i## is the corresponding value of the given set of y values and ##h_i## is defined as ##x_{i + 1} - x_i##.

The ##a## coefficients (n in total) satisfy the following n - 2 linear equations: $$h_1 a_i + 2(h_{i + 1} + h_i)a_{i + 1} + h_{i + 1}a_{i + 1} = \frac{y_{i + 2} - y_{i + 1}}{h_{i + 1}} - \frac{y_{i + 1} - y_i}{h_i}$$

So, you have n coefficients and n - 2 equations. Therefore, you need 2 extra equations to be able to solve the system.

For a natural cubic spline these end conditions are ##a_1## = 0 and ##a_n## = 0. So, you can then write the system in the form: ##Ma = d##. Where, ##M## is a tridiagonal matrix of ##h_i## along it's sub diagonal (n - 1 in length), ##h_{i + 1}## along it's super diagonal (n - 1 in length) and ## 2(h_{i + 1} + h_i)## along it's main diagonal (n in length). Thus an n x n matrix is produced. Then ##a## is the coefficient matrix of ##a_i \rightarrow a_n## (n x 1) and ##d## is the n x 1 vector filled with ## \frac{y_{i + 2} - y_{i + 1}}{h_{i + 1}} - \frac{y_{i + 1} - y_i}{h_i}##. Incorporating the extra conditions in, the first and last rows of matrix M will be 1 0 0 ... and ...0 0 0 1 respectively. As well as the first and last rows of the vector ##d## being 0. This ensures that ##a_1## and ##a_n## = 0.

So, my question is, when writing this linear system for a parabolically terminated cubic spline in matrix form, who's end conditions are ##-a_1 + a_2 = 0## and ##-a_{n-1} + a_n = 0##, how do the first and last rows of M and d change? I've outlined above how the matrices are set up for the given conditions ##a_1## = 0 and ##a_n## = 0, and I just wnat to know how they change with these new conditions.



Homework Equations


All above.


The Attempt at a Solution


All above.
 
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  • #2
SherlockOhms said:

Homework Statement


I'm trying to derive the coefficient matrix (a) of a parabolically terminated cubic spline. This is the matrix of coefficients ##a_i \rightarrow a_n## where n is the number of data points provided.

With this matrix you can find all the other coefficients (b and c) that define the spline using: $$b_i = \frac{y_i}{h_i} - a_i h_i$$ where ##y_i## is the corresponding value of the given set of y values and ##h_i## is defined as ##x_{i + 1} - x_i##.

The ##a## coefficients (n in total) satisfy the following n - 2 linear equations: $$h_1 a_i + 2(h_{i + 1} + h_i)a_{i + 1} + h_{i + 1}a_{i + 1} = \frac{y_{i + 2} - y_{i + 1}}{h_{i + 1}} - \frac{y_{i + 1} - y_i}{h_i}$$

So, you have n coefficients and n - 2 equations. Therefore, you need 2 extra equations to be able to solve the system.

For a natural cubic spline these end conditions are ##a_1## = 0 and ##a_n## = 0. So, you can then write the system in the form: ##Ma = d##. Where, ##M## is a tridiagonal matrix of ##h_i## along it's sub diagonal (n - 1 in length), ##h_{i + 1}## along it's super diagonal (n - 1 in length) and ## 2(h_{i + 1} + h_i)## along it's main diagonal (n in length). Thus an n x n matrix is produced. Then ##a## is the coefficient matrix of ##a_i \rightarrow a_n## (n x 1) and ##d## is the n x 1 vector filled with ## \frac{y_{i + 2} - y_{i + 1}}{h_{i + 1}} - \frac{y_{i + 1} - y_i}{h_i}##. Incorporating the extra conditions in, the first and last rows of matrix M will be 1 0 0 ... and ...0 0 0 1 respectively. As well as the first and last rows of the vector ##d## being 0. This ensures that ##a_1## and ##a_n## = 0.

So, my question is, when writing this linear system for a parabolically terminated cubic spline in matrix form, who's end conditions are ##-a_1 + a_2 = 0## and ##-a_{n-1} + a_n = 0##, how do the first and last rows of M and d change? I've outlined above how the matrices are set up for the given conditions ##a_1## = 0 and ##a_n## = 0, and I just wnat to know how they change with these new conditions.



Homework Equations


All above.


The Attempt at a Solution


All above.

You have already said how the first and last row change: instead of a1 = 0 you have a1-a2=0, and instead of a_n = 0 you have a_(n-1)-a_n = 0.
 
  • #3
Think I've already got it sorted. Thanks for the reply.
 

1. What is a coefficient matrix of cubic spline interpolation?

A coefficient matrix of cubic spline interpolation is a square matrix that is used to find the coefficients of a cubic spline function. It is typically represented as a system of linear equations, with each row representing a spline segment and each column representing a coefficient.

2. How is a coefficient matrix of cubic spline interpolation used?

The coefficient matrix is used to determine the coefficients of the cubic spline function, which in turn is used to interpolate data points. This allows for a smooth and continuous curve to be fitted to the data, providing a more accurate representation of the underlying relationship between the data points.

3. What are the advantages of using a coefficient matrix for cubic spline interpolation?

Using a coefficient matrix allows for a more efficient and accurate way to calculate the coefficients of the cubic spline function. It also ensures that the resulting spline curve is continuously differentiable, providing a smoother fit to the data.

4. Can a coefficient matrix be used for any type of data?

Yes, a coefficient matrix can be used for any type of data as long as it follows a continuous and smooth trend. However, it is most commonly used for interpolating data points on a curve or surface.

5. How is the accuracy of a cubic spline interpolation affected by the coefficient matrix?

The accuracy of a cubic spline interpolation is directly affected by the accuracy of the coefficients calculated from the coefficient matrix. Therefore, it is important to ensure that the matrix is calculated correctly and with sufficient precision to obtain an accurate spline curve.

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