A new framework for polynomial approximation to differential equations

06/03/2021
by   Luigi Brugnano, et al.
0

In this paper we discuss a framework for the polynomial approximation to the solution of initial value problems for differential equations. The framework, initially devised for the approximation of ordinary differential equations, is further extended to cope with constant delay differential equations. Relevant classes of Runge-Kutta methods can be derived within this framework.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/12/2020

Numerical Approximation of Nonlinear SPDE's

The numerical analysis of stochastic parabolic partial differential equa...
research
11/25/2017

Efficiently and easily integrating differential equations with JiTCODE, JiTCDDE, and JiTCSDE

We present a family of Python modules for the numerical integration of o...
research
06/17/2019

Word-series high-order averaging of highly oscillatory differential equations with delay

We show that, for appropriate combinations of the values of the delay an...
research
04/27/2023

A framework for rigorous computational methods using Haar wavelets for differential equations

This work presents a framework for a-posteriori error-estimating algorit...
research
09/04/2023

Extremal Growth of Multiple Toeplitz Operators and Implications for Numerical Stability of Approximation Schemes

We relate the power bound and a resolvent condition of Kreiss-Ritt type ...
research
01/02/2021

A New Framework for Inference on Markov Population Models

In this work we construct a joint Gaussian likelihood for approximate in...
research
08/09/2022

Interpretable Polynomial Neural Ordinary Differential Equations

Neural networks have the ability to serve as universal function approxim...

Please sign up or login with your details

Forgot password? Click here to reset