Introduction to numerical analysis: 2nd edition
Introduction to numerical analysis: 2nd edition
Minimax polynomial preconditioning for Hermitian linear systems
SIAM Journal on Matrix Analysis and Applications
Ten lectures on wavelets
On Faber polynomials generated by an m-star
Mathematics of Computation
Multidimensional Digital Signal Processing
Multidimensional Digital Signal Processing
Hi-index | 0.00 |
Let f(z) be a continuous function defined on the compact set K@?C and let E"n(f)=E"n(f,K) be the degree of approximation to f, for the supremum norm on K, by polynomials of degree (at most) n. ThusE"n(f,K)=infP@?P"n@?f-P@?.Here P"n denotes the space of polynomials of degree at most n and @?.@? is the supremum norm on K. For a positive integer s and for 0~E"n(f,K)^1^n=b^s^2-a^s^2b^s^2+a^s^2s,thus recovering several classical results. The proof of this error estimate is then translated into an algorithm that finds the polynomial of near best approximation.