High-significance Averages of Event-Related Potential via Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InCollection{Citi:2009:GPTP,
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author = "Luca Citi and Riccardo Poli and Caterina Cinel",
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title = "High-significance Averages of Event-Related Potential
via Genetic Programming",
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booktitle = "Genetic Programming Theory and Practice {VII}",
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year = "2009",
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editor = "Rick L. Riolo and Una-May O'Reilly and
Trent McConaghy",
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series = "Genetic and Evolutionary Computation",
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address = "Ann Arbor",
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month = "14-16 " # may,
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publisher = "Springer",
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chapter = "9",
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pages = "135--157",
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keywords = "genetic algorithms, genetic programming, Event-related
potentials, Register-based GP, Memory-with-Memory",
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isbn13 = "978-1-4419-1653-2",
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DOI = "doi:10.1007/978-1-4419-1626-6_9",
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abstract = "In this paper we use register-based genetic
programming with memory-with memory to discover
probabilistic membership functions that are used to
divide up data-sets of event-related potentials
recorded via EEG in psycho-physiological experiments
based on the corresponding response times. The
objective is to evolve membership functions which lead
to maximising the statistical significance with which
true brain waves can be reconstructed when averaging
the trials in each bin. Results show that GP can
significantly improve the fidelity with which ERP
components can be recovered.",
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notes = "part of \cite{Riolo:2009:GPTP}",
- }
Genetic Programming entries for
Luca Citi
Riccardo Poli
Caterina Cinel
Citations