Markov L2 inequality with the Gegenbauer weight
Abstract
For the Gegenbauer weight function wλ(t)=(1-t2)λ-1/2, λ>-1/2, we denote by ·wλ the associated L2-norm, fwλ:=(∫-11wλ(t)f2(t)\,dt)1/2. We study the Markov inequality pwλ≤ cn(λ)\, pwλ, p∈ Pn, where Pn is the class of algebraic polynomials of degree not exceeding n. Upper and lower bounds for the best Markov constant cn(λ) are obtained, which are valid for all n∈ N and λ>-12.
0
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.