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For polynomials in two or more variables, the degree of a term is the sum of the exponents of the variables in the term; the degree (sometimes called the total degree) of the polynomial is again the maximum of the degrees of all terms in the polynomial. For example, the polynomial x 2 y 2 + 3x 3 + 4y has degree 4, the same degree as the term x ...
Runge's phenomenon shows that for high values of n, the interpolation polynomial may oscillate wildly between the data points. This problem is commonly resolved by the use of spline interpolation. Here, the interpolant is not a polynomial but a spline: a chain of several polynomials of a lower degree.
The n roots of a polynomial of degree n depend continuously on the coefficients. For simple roots, this results immediately from the implicit function theorem.This is true also for multiple roots, but some care is needed for the proof.
In the case of polynomials in more than one indeterminate, a polynomial is called homogeneous of degree n if all of its non-zero terms have degree n. The zero polynomial is homogeneous, and, as a homogeneous polynomial, its degree is undefined. [c] For example, x 3 y 2 + 7x 2 y 3 − 3x 5 is homogeneous of degree 5. For more details, see ...
Any general polynomial of degree n = + + + + (with the coefficients being real or complex numbers and a n ≠ 0) has n (not necessarily distinct) complex roots r 1, r 2, ..., r n by the fundamental theorem of algebra.
A Bernstein polynomial can always be written as a linear combination of polynomials of higher degree: , =, + + +, (). The expansion of the Chebyshev Polynomials of the First Kind into the Bernstein basis is [ 3 ] T n ( u ) = ( 2 n − 1 ) ! ! ∑ k = 0 n ( − 1 ) n − k ( 2 k − 1 ) ! !
Given n + 1 points, there is a unique polynomial of degree ≤ n which goes through the given points. Neville's algorithm evaluates this polynomial. Neville's algorithm is based on the Newton form of the interpolating polynomial and the recursion relation for the divided differences.
In numerical analysis, the Lagrange interpolating polynomial is the unique polynomial of lowest degree that interpolates a given set of data. Given a data set of coordinate pairs ( x j , y j ) {\displaystyle (x_{j},y_{j})} with 0 ≤ j ≤ k , {\displaystyle 0\leq j\leq k,} the x j {\displaystyle x_{j}} are called nodes and the y j ...