Matrix-valued rational minimax approximants with a common denominator are proved to exist on dense point sets, with Kolmogorov/Ruttan optimality certificates and an equivalence to the m-d-Lawson dual conditions.
Title resolution pending
3 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
3
Pith papers citing it
3
external citations · Crossref
representative citing papers
The paper develops a duality-based framework and an iterative algorithm (m-d-Lawson) for discrete minimax rational approximation of matrix-valued functions with a common denominator.
b-d-Lawson combines barycentric rational representation with a dual optimization framework to solve interpolation-constrained rational minimax approximation via Lawson's iteration.
citing papers explorer
-
Rational Minimax Approximations for Matrix-Valued Functions: Existence, Optimality and Algorithms
Matrix-valued rational minimax approximants with a common denominator are proved to exist on dense point sets, with Kolmogorov/Ruttan optimality certificates and an equivalence to the m-d-Lawson dual conditions.
-
Rational minimax approximation of matrix-valued functions
The paper develops a duality-based framework and an iterative algorithm (m-d-Lawson) for discrete minimax rational approximation of matrix-valued functions with a common denominator.
-
Interpolation constrained rational minimax approximation with barycentric representation
b-d-Lawson combines barycentric rational representation with a dual optimization framework to solve interpolation-constrained rational minimax approximation via Lawson's iteration.