A multiresolution algorithm to approximate the Hutchinson measure for IFS and GIFS

TL;DR

This paper presents a new multiresolution algorithm to approximate the Hutchinson measure for IFS and GIFS, enhancing attractor generation methods for both classical and fuzzy systems.

Contribution

It introduces a discrete algorithm that complements existing deterministic methods for approximating measures in IFS and GIFS.

Findings

Effective approximation of Hutchinson measure demonstrated

Algorithm applicable to both classical and fuzzy IFS/GIFS

Enhances multiresolution analysis for attractor generation

Abstract

We introduce the discrete version of the Hutchinson--Barnsley theory providing algorithms to approximate the Hutchinson measure for iterated function systems (IFS) and generalized iterated function systems (GIFS) complementing the discrete version of the deterministic algorithm considered in our previous work DOS to generate attractors of both classical and fuzzy IFS and GIFS.