@inproceedings{7510348b9c9649289a82b821c5222ef6,

title = "Recurrent self-similarities and machine learning: The inverse problem of building fractals",

abstract = "A method to analyse recurrent similarities, or self-similarities, in higher dimensional data set, is proposed in this paper. An algorithm capable of solving the inverse problem of building a fractal is detailed. The latter is constituted of three parts: the decomposition of the data into subsets; the determination of a simple IFS from these sets; the reconstruction of the attractor. Basic attractors of fractals are reconstructed using these IFS, with a small error.",

keywords = "Data Mining, Fractals, Inverse problem, Iterated Function System, Neural Network",

author = "Timothee Leleu and Akito Sakurai",

year = "2009",

month = jan,

day = "1",

language = "English",

series = "Mendel",

publisher = "Brno University of Technology",

pages = "139--146",

editor = "Matousek Radek",

booktitle = "Mendel",

note = "15th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2009 ; Conference date: 24-06-2009 Through 26-06-2009",

}