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Resolution of the inverse problem for iterated function systems using Evolutionary Algorithms

Authors: Sarafopoulos, A. and Buxton, B.

Pages: 1071-1078

Abstract:

The resolution of the inverse problem for iterated function systems (IFS) is a problem that has remained open, currently there is no general solution that requires no human interaction and provides optimal results. Here we present a novel approach to the resolution of the general inverse problem for IFS using segmentation of target images in conjuction with an Evolutionary Algorithm that is a Genetic Programming-Evolutionary Strategies hybrid. © 2006 IEEE.

Source: Scopus

Resolution of the inverse problem for iterated function systems using Evolutionary Algorithms

Authors: Sarafopoulos, A. and Buxton, B.

Pages: 1056-+

ISBN: 978-0-7803-9487-2

Source: Web of Science (Lite)

Resolution of the Inverse Problem for Iterated Function Systems using Evolutionary Algorithms

Authors: Sarafopoulos, A. and Buxton, B.

Editors: Yen, G.G., Lucas, S.M., Fogel, G., Kendall, G., Salomon, R., Zhang, B.-T., Coello, C.A. and Runarsson, T.P.

Pages: 1071-1078

Publisher: IEEE Press

Place of Publication: New York

Abstract:

The resolution of the inverse problem for iterated function systems (IFS) is a problem that has remained open, currently there is no general solution that requires no human interaction and provides optimal results. Here we present a novel approach to the resolution of the general inverse problem for IFS using segmentation of target images in conjuction with an Evolutionary Algorithm that is a Genetic Programming-Evolutionary Strategies hybrid

http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=11108

Source: Manual

Preferred by: Ari Sarafopoulos