The estimation of h\"olderian regularity using genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Trujillo:2010:gecco,
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author = "Leonardo Trujillo and Pierrick Legrand and
Jacques Levy-Vehel",
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title = "The estimation of h{\"{o}}lderian regularity using
genetic programming",
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booktitle = "GECCO '10: Proceedings of the 12th annual conference
on Genetic and evolutionary computation",
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year = "2010",
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editor = "Juergen Branke and Martin Pelikan and Enrique Alba and
Dirk V. Arnold and Josh Bongard and
Anthony Brabazon and Juergen Branke and Martin V. Butz and
Jeff Clune and Myra Cohen and Kalyanmoy Deb and
Andries P Engelbrecht and Natalio Krasnogor and
Julian F. Miller and Michael O'Neill and Kumara Sastry and
Dirk Thierens and Jano {van Hemert} and Leonardo Vanneschi and
Carsten Witt",
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isbn13 = "978-1-4503-0072-8",
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pages = "861--868",
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keywords = "genetic algorithms, genetic programming, Signal
regularity, Holder exponent",
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month = "7-11 " # jul,
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organisation = "SIGEVO",
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address = "Portland, Oregon, USA",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.3708",
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URL = "http://hal.inria.fr/docs/00/53/89/43/PDF/t10fp182-trujillo.pdf",
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DOI = "doi:10.1145/1830483.1830641",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "This paper presents a Genetic Programming (GP)
approach to synthesise estimators for the pointwise
Holder exponent in 2D signals. It is known that
irregularities and singularities are the most salient
and informative parts of a signal. Hence, explicitly
measuring these variations can be important in various
domains of signal processing. The point wise Holder
exponent provides a characterisation of these types of
features. However, current methods for estimation
cannot be considered to be optimal in any sense.
Therefore, the goal of this work is to automatically
synthesise operators that provide an estimation for the
Holderian regularity in a 2D signal. This goal is posed
as an optimisation problem in which we attempt to
minimize the error between a prescribed regularity and
the estimated regularity given by an image operator.
The search for optimal estimators is then carried out
using a GP algorithm. Experiments confirm that the
GP-operators produce a good estimation of the Holder
exponent in images of multifractional Brownian motions.
In fact, the evolved estimators significantly
outperform a traditional method by as much as one order
of magnitude. These results provide further empirical
evidence that GP can solve difficult problems of
applied mathematics.",
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notes = "Also known as \cite{1830641} GECCO-2010 A joint
meeting of the nineteenth international conference on
genetic algorithms (ICGA-2010) and the fifteenth annual
genetic programming conference (GP-2010)",
- }
Genetic Programming entries for
Leonardo Trujillo
Pierrick Legrand
Jacques Levy-Vehel
Citations