
doi: 10.1007/bf01874691
The author deals with Hermite interpolation polynomials of the form \[ H_{mn} (f,x):= \sum_{k=1}^ n \sum_{j=0}^{m-1} f^{(j)} (x_{kn}) A_{jk}(x) \] for a function \(f\) that is \(m-1\) times continuously differentiable on the interval \([-1,1]\) (\(m\) an arbitrary positive integer) and a system of arbitrary interpolation nodes \(-1\leq x_{nn}< x_{n-1,n}< \cdots< x_{1n}\leq 1\). The fundamental polynomials \(A_{jk}(x)\) of degree at most \(mn-1\) satisfy the conditions \(A_{jk}^{(p)} (x_{qn})= \delta_{jp} \delta_{kq}\) for \(j,p= 0,\dots, m-1\) and \(k,q= 1,\dots, n\). As the main result of the paper, exact lower bounds for the quantities \(L_{jmn}:= \| \sum_{k=1}^ n | A_{jk}(x)| \|_ \infty\), \(j=0,\dots, m-1\), are established, namely \(L_{jmn}\geq c_ 1(\log n)/ n^ j\) if \(m-j\) is even, with \(c_ 1\) and \(c_ 2\) being positive constants depending only on \(j\) and \(m\). The Chebyshev nodes \(x_{kn}= \cos((2k-1) \pi/(2n))\) are used to show that these estimates are sharp.
Hermite interpolation polynomials, Approximation by polynomials, Chebyshev nodes, Interpolation in approximation theory
Hermite interpolation polynomials, Approximation by polynomials, Chebyshev nodes, Interpolation in approximation theory
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