Títol:
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Robust unsupervised detection of action potentials with probabilistic models
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Autor/a:
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Benítez Iglesias, Raúl; Nenadic, Zoran
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Altres autors:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. NOLIN - Física No-Lineal i Sistemes Fora de l'Equilibri |
Abstract:
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We develop a robust and fully unsupervised algorithm
for the detection of action potentials from extracellularly recorded
data. Using the continuous wavelet transform allied to probabilistic
mixture models and Bayesian probability theory, the detection of
action potentials is posed as a model selection problem. Our technique
provides a robust performance over a wide range of simulated
conditions, and compares favorably to selected supervised
and unsupervised detection techniques. |
Abstract:
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Peer Reviewed |
Matèries:
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-Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat -Bayesian statistical decision theory -Action potentials -Bayesian probability theory -Continuous wavelet transform -Expectation maximization algorithm -Finite mixture models -Maximum likelihood principle -Estadística bayesiana |
Drets:
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Tipus de document:
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Article - Versió actualitzada Article |
Publicat per:
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Institute of Electrical and Electronics Engineers
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