A Linear Spline Markov Approximation Method for Random Maps with Position Dependent Probabilities

Document Type

Article

Publication Date

3-1-2020

Department

Mathematics

School

Mathematics and Natural Sciences

Abstract

We present a rigorous convergence analysis of a linear spline Markov finite approximation method for computing stationary densities of random maps with position dependent probabilities, which consist of several chaotic maps. The whole analysis is based on a new Lasota–Yorke-type inequality for the Markov operator associated with the random map, which is better than the previous one in the literature and much simpler to obtain. We also present numerical results to support our theoretical analysis.

Publication Title

International Journal of Bifurcation and Chaos

Volume

30

Issue

3

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