2009 | OriginalPaper | Chapter
Convergence Rate Analysis
Authors : Jiu Ding, Aihui Zhou
Published in: Statistical Properties of Deterministic Systems
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
After showing the convergence of the two numerical methods for Frobenius-Perron operators in the previous chapter, we further investigate the convergence rate problem for them. Keller’s stochastic stability result for a class of Markov operators will be studied first, which leads to his first proof of the
L
1
-norm convergence rate
O
(ln
n/n
) for Ulam’s method applied to the Lasota-Yorke class of mappings. Then we introduce Murrary’s work on an explicit upper bound of the convergence rate for Ulam’s method. The convergence rate analysis for the piecewise linear Markov method under the
BV
-norm will be presented in the last section.