lecture notes on polynomial interpolation
1 Summary of notation and terminonlogy
- •
multi-evaluation mapping: . Here is the vector space
of polynomials ofdegree or less.
- •
interpolation mapping: where aredistinct;
- •
Vandermonde matrix
and polynomial;
- •
overdetermined and underdetermined linear system;
- •
overdetermined and underdetermined interpolation
problem
2 The polynomial interpolation problem
Definition 1.
Let be given. Define , the multi-evaluation mapping, to be the lineartransformation given by
Problem 2 (Polynomial interpolation).
Given to find a polynomial such that . Equivalently, given to find thepreimage .
Theorem 3.
Fix . The multi-evaluation mapping is an isomorphism if and onlyif the components
are distinct.
3 Vandermonde matrix, polynomial, and determinant
Definition 4.
For a given , the following matrix
is calledthe Vandermonde matrix. Theexpression,
is called the Vandermonde polynomial. Note: we define ; the usual convention is that the empty product is equal to .
Proposition 5.
The Vandermonde matrix is the transformation matrix of with themonomial basis as the input basis and thestandard basis as the output basis.
Theorem 6.
The Vandermonde polynomial gives the determinant of the Vandermondematrix:
(1) |
or more succinctly,
Proof.
We will prove formula (1) by induction
on . Notethat
Evidently then, theformula works for . Next, suppose that we believe the formulafor a given . We show that the formula is valid for . For and a variable , and consider the degree polynomial
By the properties of determinants, are roots of. Taking the cofactor expansion along the bottom row, wesee that the coefficient of is .Therefore,
as was to be shown.∎
4 Lagrange interpolation formula
Let be distinct. We know that is invertible. Let denote the inverse
. In principle,this inverse is described by the inverse of the Vandermonde matrix.Is there another way to solve the interpolation problem? For let us define the polynomial
These degree polynomials have been “engineered” so that andso that for
Theorem 7 (Lagrange interpolation formula).
Let be distinct. Then,
5 Underdetermined and overdetermined interpolation
Definition 8.
Let be a linear transformation of finite dimensionalvector spaces. A linear problem is an equation of the form
where is given, and isthe unknown. To be more precise, the problem is to determinethe preimage for a given . We say that theproblem is overdetermined if , i.e. if thereare more equations than unknowns. The linear problem is said to beunderdetermined if , i.e., if there are morevariables than equations.
Remark 9.
By the rank-nullity theorem, anunderdetermined linear problem will either be inconsistent, or willhave multiple solutions. Thus, an underdetermined system arises when is not one-to-one; i.e., the kernel is non-trivial. Anoverdetermined linear system is inconsistent, unless satisfies anumber linear compatibility constraints, equations that describe the image. To put it another way, an overdetermined system ariseswhen is not onto.
Definition 10.
Let be distinct and let be the corresponding multi-evaluationmapping. Let be given. The linear equation
is called an underdetermined interpolation problem if .If , we call the above equation an overdeterminedinterpolation problem. Note that if , the interpolationproblem is “just right”; there is exactly one solution, namely thepolynomial given by the Lagrange interpolation formula.
Proposition 11 (Underdetermined interpolation).
Let be distinct. Define
to be the degree polynomial with the as its roots.Suppose that . Then,the multi-evaluation mapping is not one-to-one. A basis for thekernel is given by . Let be given. The solutionset to the interpolation problem , is given by
whereis the degree polynomial given by the Lagrangeinterpolation formula. To put it another way, the general solutionof the equation
is given by
Proposition 12 (Overdetermined interpolation).
Let be distinct.Suppose that . Then,the multi-evaluation mapping is not onto. If , then belongs to if and only if
More generally, for any , the interpolation problem has a solution if and onlyif where
Remark 13.
The compatibility constraints on for an overdetermined system amount to the conditionthat lie in the image of , or what is equivalent,belong to the column space of the corresponding transformation matrix.We can therefore obtain the constraint equations by row reducing theaugmented matrix to echelon form
. The back entries ofthe last rows will hold the constraint equations.Equivalently, we can solve the interpolation problem for to obtain a . The additional equations
are the desired compatibility constraints on .