A machine learning approach to the analysis of time-frequency maps, and its application to neural dynamics
- Author
- VIALATTE, Francois B1 2 ; MARTIN, Claire2 ; DUBOIS, Rémi1 ; HADDAD, Joëlle1 ; QUENET, Brigitte1 ; GERVAIS, Rémi2 ; DREYFUS, Gérard1
[1] École Supérieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI-Paristech), Laboratoire d'Électronique (UMR 7084 CNRS). 10 rue Vauquelin, 75005 Paris, France
[2] Institut des Sciences Cognitives (ISC), UMR 5015 CNRS Université Claude Bernard Lyon 169675 Bron and IFR 19 Neurosciences, Lyon, France - Source
Neural networks. 2007, Vol 20, Num 2, pp 194-209, 16 p ; ref : 1/2 p
- ISSN
- 0893-6080
- Scientific domain
- Electronics; Computer science; Neurology
- Publisher
- Elsevier Science, Oxford
- Publication country
- United Kingdom
- Document type
- Article
- Language
- English
- Author keyword
- Bump Electro-encephalography Local field potential Machine learning Neural network Odour recognition Olfaction Rat Time-frequency Wavelet
- Keyword (fr)
- Analyse fréquence temps Analyse statistique Animal Bulbe olfactif Cerveau Complexité temps Electrophysiologie Encéphale Homme Information utile Intelligence artificielle Modélisation Méthode statistique Olfaction Paramètre statistique Potentiel champ Rat Signal complexe Similitude Système nerveux central Traitement signal Variabilité Fonction élémentaire Mammalia Rodentia Vertebrata
- Keyword (en)
- Time-frequency analysis Statistical analysis Animal Olfactory bulb Brain Time complexity Electrophysiology Encephalon Human Useful information Artificial intelligence Modeling Statistical method Olfaction Statistical parameter Field potential Rat Complex signal Similarity Central nervous system Signal processing Variability Elementary function Mammalia Rodentia Vertebrata
- Keyword (es)
- Análisis estadístico Animal Bulbo olfatorio Cerebro Complejidad tiempo Electrofisiología Encéfalo Hombre Información útil Inteligencia artificial Modelización Método estadístico Olfación Parámetro estadístico Potencial campo Rata Señal compleja Similitud Sistema nervioso central Procesamiento señal Variabilidad Función elemental Mammalia Rodentia Vertebrata
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02B Software / 001D02B07 Memory organisation. Data processing / 001D02B07D Information systems. Data bases
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C02 Learning and adaptive systems
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C06 Connectionism. Neural networks
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D04 Telecommunications and information theory / 001D04A Information, signal and communications theory / 001D04A03 Information theory
- Discipline
- Computer science : theoretical automation and systems Telecommunications and information theory
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 18589581
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.neunet.2006.09.013 
https://dx.doi.org/10.1016/j.neunet.2006.09.013
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