Bernstein polynomial

For $f\in C([0,1{]}^d)$, its tensor-product Bernstein polynomial is the expectation of $f(X_1/n,\dots ,X_d/n)$ for independent binomial variables $X_j\sim \mathrm{Bin}(n,x_j)$. Uniform continuity and concentration of the binomial variables prove uniform convergence to $f$.

For $m\ge 1$ and $n\ge 2$, the Bernstein polynomial of the monomial $x^m$ satisfiesIt follows by applying $k\left(\genfrac{}{}{0ex}{}{n}{k}\right)=n\left(\genfrac{}{}{0ex}{}{n-1}{k-1}\right)$ and expanding $k=(k-1)+1$ with the binomial theorem. The coefficients sum to one; only the first tends to one as $n\to \infty$. Induction on $m$ proves uniform convergence of these monomial approximants, starting from $B_n(1)=1$.

On the fixed finite-dimensional space of polynomials of degree at most $d$, uniform convergence of $B_n$ on each monomial and equivalence of norms in finite dimensions imply ${\epsilon }_n=\Vert B_n-I{\Vert }_{\mathrm{op}}\to 0$. A Neumann series then gives $\Vert B_n^{-1}-I{\Vert }_{\mathrm{op}}\le {\epsilon }_n/(1-{\epsilon }_n)$ for sufficiently large $n$. Consequently the displayed convergence holds. A strictly positive polynomial has positive minimum on the compact interval, so its inverse Bernstein approximants are also strictly positive for all sufficiently large $n$.

These $n+1$ nonnegative polynomials form a basis of polynomials of degree at most $n$, and sum to one on $[0,1]$. For $0\le j\le n$,where ratios for $j=0$ equal one and terms with $k<j$ vanish. The identity follows from $\left(\genfrac{}{}{0ex}{}{n}{k}\right)(k{)}_j/(n{)}_j=\left(\genfrac{}{}{0ex}{}{n-j}{k-j}\right)$ and the binomial theorem. It gives explicit basis coefficients using the falling factorial.

If a polynomial $f$ is strictly positive on $[0,1]$, take $g_n=B_n^{-1}f$. By inverse Bernstein approximation on a fixed-degree polynomial space, eventually $g_n>0$ on the interval. Thereforehas strictly positive coefficients. The converse implication to nonnegativity follows immediately because each basis term is nonnegative. Strict positivity is essential for the general existence result: a nonzero polynomial vanishing at an interior point cannot have a nonnegative-coefficient representation in this basis, whose individual terms are positive throughout the open interval.

Write $f={\sum }_k{\beta }_{k,n}{b}_{k,n}$ in the Bernstein basis. Representing the same polynomial at degrees $n$ and $n+1$ gives the displayed convex combinations for internal indices; the endpoint coefficients are copied. Therefore the minimum coefficient cannot decrease under degree elevation. In the unnormalized basis $x^k(1-x{)}^{n-k}$, the elevated coefficients are $c_k^{\prime }=c_{k-1}+c_k$ with the corresponding endpoint convention, so nonnegativity certificates are preserved.