We prove convergence of two algorithms approximating invariant measures to iterated function systems numerically. We consider IFSs with finitely many continuous and injective non-overlapping maps on the unit interval. The first algorithm is a version of the Ulam algorithm for IFSs introduced by Strichartz et al. [16]. We obtain convergence in the supremum metric for distribution functions of the approximating eigen-measures to a unique invariant measure for the IFS. We have to make some modifications of the usual way of treating the Ulam algorithm due to a problem concerning approximate eigenvalues, which is part of our more general situation with weights not necessarily being related to the maps of the IFS. The second algorithm is a new recursive algorithm which is an analogue of forward step algorithms in the approximation theory of ODEs. It produces a sequence of approximating measures that converges to a unique invariant measure with geometric rate in the supremum metric. The main advantage of the recursive algorithm is that it runs much faster on a computer (using Maple) than the Ulam algorithm.
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