Uniqueness of Cubic Spline Interpolation: How Can We Prove It?

In summary, we have discussed the interpolation exercise for cubic splines with $m$ segments and $4m$ coefficients. To find these coefficients, we need $4m$ independent equations, which can be obtained from the given points and conditions of continuity. The resulting spline function $s(x)$ is defined as a composite function with piecewise polynomial functions $s_i(x)$ for each segment. The conditions of continuity require that $s_i(0)=s(i-1)$ and $s_i(1)=s(i)$ for each segment, and also $s_i(x_i)=s_{i+1}(x_i)$ for $i=1,\ldots,m-1$.
  • #1
mathmari
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Hey! 😊

Show that the interpolation exercise for cubic splines with $s(x_0), s(x_1), , \ldots , s(x_m)$ at the points $x_0<x_1<\ldots <x_m$, together with one of $s'(x_0)$ or $s''(x_0)$ and $s'(x_m)$ or $s''(x_m)$ has exactly one solution.

Could you give me a hint how we could show that? Do wwe have to assume that we have two different solutions annd get a contradiction? :unsure:
 
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  • #2
A cubic spline for a segment has 4 coefficients. Since we have $m$ segments, we have $4m$ coefficients.
To find them, we need $4m$ independent equations.
Which equations do we have? 🤔
 
  • #3
Klaas van Aarsen said:
A cubic spline for a segment has 4 coefficients. Since we have $m$ segments, we have $4m$ coefficients.
To find them, we need $4m$ independent equations.
Which equations do we have? 🤔

We have the equations $s(x_0), s(x_1), \ldots , s(x_m)$, then we have also conditions of continuity, or not? And we have also the conditions $s'(x_0)=s'(x_m)$ or $s''(x_0)=s''(x_m)$.

Is that correct? :unsure:
 
  • #4
Yes, we have the conditions of continuity.
Each of the $m$ segments must have the given starting and ending points, which gives us $2m$ independent equations, doesn't it? 🤔

Don't we also have the condition that the derivative must be continuous? That is, no angles in the resulting spline? 🤔
 
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  • #5
Klaas van Aarsen said:
Yes, we have the conditions of continuity.
Each of the $m$ segments must have the given starting and ending points, which gives us $2m$ independent equations, doesn't it? 🤔

Don't we also have the condition that the derivative must be continuous? That is, no angles in the resulting spline? 🤔

I got stuck right now. We don't have an index at $s(x)$. Does this mean that at each segment we have the same function? Shouldn't it be $s_i(x)$ ? :unsure:
 
  • #6
mathmari said:
I got stuck right now. We don't have an index at $s(x)$. Does this mean that at each segment we have the same function? Shouldn't it be $s_i(x)$ ?

Hmm... your OP says "the interpolation exercise for cubic splines". Which interpolation exercise is that? 🤔

Note that a "cubic" spline is a third order polynomial, which means that it has 4 coefficients.
Consequently if there are more than 4 points, we cannot find one that has all points on its curve.
So either the spline is actually of $m$-th order, or the spline consists of $m$ segments each with its own coefficients, or the spline is a best-fit function.
Btw, even if it is a best-fit function, a "cubic" spline should still have only at most 4 points given and not $m+1$ points.
And if it were an $m$-th order polynomial, then there is no need to set constraints on the first or second derivative at the end points.
So I assumed we have a set of $m$ cubic splines, which I guess may not be what is intended.

If not, can you tell that kind of spline we are talking about then? 🤔
There are many types after all.
 
  • #7
mathmari said:
I got stuck right now. We don't have an index at $s(x)$. Does this mean that at each segment we have the same function? Shouldn't it be $s_i(x)$ ?

The spline function $s$ would be a composite function.
That is:
$$s(x)=\begin{cases}s_1(x)&\text{if } 0\le x < 1 \\ s_2(x-1) &\text{if } 1\le x < 2 \\\ldots\\ s_m(x-m+1) &\text{if } m-1\le x \le m\end{cases}$$
where $s_i(u)=a_{i,3} u^3 + a_{i,2} u^2 + a_{i,1} u + a_{i,0}$ for $i=1,\ldots,m$.

So we don't simply have $s_i(x)$ since it depends on the value of $x$, which $s_i$ we need. 🤔

Suppose we assume that this is indeed what was intended. Then a solution is a set of coefficients $a_{i,j}$.

To ensure continuity, we need that $s_i(0)=s(i-1)$ and $s_i(1)=s(i)$ for $i=1,\ldots,m$. These are $2m$ independent equations.
To ensure continuity of the derivative, we need $s_i'(1)=s_{i+1}'(0)$ for $i=1,\ldots,m-1$. These are $2m-2$ independent equations.
So we are 2 equations short to find all coefficients.
If we add equations with the values of $s_1'(0)$ and $s_m'(1)$ we have a complete independent set with a unique solution.
Alternatively we can add equations with the values of $s_1''(0)$ and $s_m''(1)$ and we have again a complete independent set with a unique solution. 🤔

In practice the boundary condition $s_1''(0)=s_m''(1)=0$ is a typical choice.
 
  • #8
Klaas van Aarsen said:
The spline function $s$ would be a composite function.
That is:
$$s(x)=\begin{cases}s_1(x)&\text{if } 0\le x < 1 \\ s_2(x-1) &\text{if } 1\le x < 2 \\\ldots\\ s_m(x-m+1) &\text{if } m-1\le x \le m\end{cases}$$
where $s_i(u)=a_{i,3} u^3 + a_{i,2} u^2 + a_{i,1} u + a_{i,0}$ for $i=1,\ldots,m$.

Why is the function defined in that form, I mean the argument is "x-something" and not $$s(x)=\begin{cases}s_1(x)&\text{if } 0\le x < 1 \\ s_2(x) &\text{if } 1\le x < 2 \\\ldots\\ s_m(x) &\text{if } m-1\le x \le m\end{cases}$$
Klaas van Aarsen said:
To ensure continuity, we need that $s_i(0)=s(i-1)$ and $s_i(1)=s(i)$ for $i=1,\ldots,m$. These are $2m$ independent equations.

Do we not get from the continuity the condition $s_i(x_i)=s_{i+1}(x_i)$ ? :unsure:
 
  • #9
mathmari said:
Why is the function defined in that form, I mean the argument is "x-something" and not $$s(x)=\begin{cases}s_1(x)&\text{if } 0\le x < 1 \\ s_2(x) &\text{if } 1\le x < 2 \\\ldots\\ s_m(x) &\text{if } m-1\le x \le m\end{cases}$$
My mistake, it should be:
$$s(x)=\begin{cases}s_1(x)&\text{if } x_0\le x < x_1 \\ s_2(x) &\text{if } x_1\le x < x_2 \\\ldots\\ s_m(x) &\text{if } x_{m-1}\le x \le x_m\end{cases}$$
🤔

Do we not get from the continuity the condition $s_i(x_i)=s_{i+1}(x_i)$ ?
Yes, with the new version of the function $s$ that is indeed the continuity condition. 🤔
 
  • #10
Klaas van Aarsen said:
My mistake, it should be:
$$s(x)=\begin{cases}s_1(x)&\text{if } x_0\le x < x_1 \\ s_2(x) &\text{if } x_1\le x < x_2 \\\ldots\\ s_m(x) &\text{if } x_{m-1}\le x \le x_m\end{cases}$$
🤔

Yes, with the new version of the function $s$ that is indeed the continuity condition. 🤔

So we have the following:
\begin{equation*}s(x)=\begin{cases}s_1(x)&\text{wenn } x_0\le x < x_1 \\ s_2(x) &\text{wenn } x_1\le x < x_2 \\\ldots\\ s_m(x) &\text{wenn } x_{m-1}\le x \le x_m\end{cases}\end{equation*}
with $s_i(x)=a_{i,3} x^3 + a_{i,2} x^2 + a_{i,1} x + a_{i,0}$ for $i=1,\ldots,m$.

A cibic spline is $C^2$, so the second derivative must be continuous.

So that the function is continuous we need $s_i(x_i)=s_{i+1}(x_i)$ for $i=1,\ldots,m-1$ and $s_i(x_{i-1})=s(x_{i-1})$ for $i=1,\ldots,m+1$.
So we have $(m-1)+(m+1)=2m$ independent equations.

So that the first derivative is continuous we need $s_i'(x_i)=s_{i+1}'(x_i)$ for $i=1,\ldots,m-1$.
So we have $m-1$ independent equations.

So that the second derivative is continuous we need $s_i''(x_i)=s_{i+1}''(x_i)$ for $i=1,\ldots,m-1$.
So we have $m-1$ independent equations.

Till now we have $2m+(m-1)+(m-1)=4m-2$ conditions (equations).

The remaining two conditions are the two possible pairs given at the statement. Is everything correct? :unsure:
 
  • #11
Looks good enough to me. (Nod)
 
  • #12
Klaas van Aarsen said:
Looks good enough to me. (Nod)

Great! Thank you very much! (Smile)
 

FAQ: Uniqueness of Cubic Spline Interpolation: How Can We Prove It?

What are cubic splines and how are they used?

Cubic splines are a type of mathematical function that is commonly used in data interpolation and curve fitting. They are made up of multiple cubic polynomials that are joined together at specific points, called knots. These splines are used to create a smooth curve that accurately represents a set of data points.

What does uniqueness mean in the context of cubic splines?

Uniqueness in the context of cubic splines refers to the fact that there is only one set of cubic polynomials that can be used to create a specific spline curve. This means that given a set of data points and a set of knots, there is only one possible way to create a smooth curve that passes through all the points and satisfies certain conditions.

Why is uniqueness important in cubic splines?

Uniqueness is important in cubic splines because it ensures that the resulting curve is well-defined and does not have multiple solutions. This means that the spline curve will accurately represent the data and will not have any unexpected or erroneous behavior.

Are there any cases where uniqueness may not hold for cubic splines?

Yes, there are some cases where uniqueness may not hold for cubic splines. This can happen when the knots are not well-distributed or when there are too few knots for the given data. In these cases, there may be multiple sets of cubic polynomials that can create a smooth curve that passes through the data points.

How can uniqueness be ensured in cubic splines?

To ensure uniqueness in cubic splines, it is important to carefully choose the number and placement of knots. The knots should be evenly distributed and there should be enough knots to accurately capture the behavior of the data. Additionally, using certain constraints, such as specifying the first and second derivatives at the endpoints, can also help ensure uniqueness.

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