Výsledky vyhledávání - "Polynomial transforms"

Akademický článek

Classification of EEG signals for epileptic seizures detection and eye states identification using Jacobi polynomial transforms-based measures of complexity and least-square support vector machine

Autor: Laurent Chanel Djoufack Nkengfack, Daniel Tchiotsop, Romain Atangana, Valérie Louis-Door, Didier Wolf

Publikováno v: Informatics in Medicine Unlocked, Vol 23, Iss , Pp 100536- (2021)

Background and objectives: Epilepsy is the most prevalent neurological disorder in humans which is characterized by recurrent seizures resulting in neurologic, cognitive, psychological and social consequences. In addition, the automatic identificatio

Externí odkaz: https://doaj.org/article/c15a65032c534fbfa2deb073a3ec4a36

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Akademický článek

A comparison study of polynomial-based PCA, KPCA, LDA and GDA feature extraction methods for epileptic and eye states EEG signals detection using kernel machines

Autor: Laurent Chanel Djoufack Nkengfack, Daniel Tchiotsop, Romain Atangana, Beaudelaire Saha Tchinda, Valérie Louis-Door, Didier Wolf

Publikováno v: Informatics in Medicine Unlocked, Vol 26, Iss , Pp 100721- (2021)

Background and objective: Initially, analysis of Electroencephalogram (EEG) signals was purely visual, tedious, time-consuming, and required a physician. Changing this old approach to classification proves to be an extraordinary task that gained much

Externí odkaz: https://doaj.org/article/bf7f877536d4432bbf5aa40bdb6b6459

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Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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A comparison study of polynomial-based PCA, KPCA, LDA and GDA feature extraction methods for epileptic and eye states EEG signals detection using kernel machines

Autor: Beaudelaire Saha Tchinda, Daniel Tchiotsop, Romain Atangana, Laurent Chanel Djoufack Nkengfack, Didier Wolf, Valérie Louis-Door

Publikováno v: Informatics in Medicine Unlocked, Vol 26, Iss, Pp 100721-(2021)

Background and objective Initially, analysis of Electroencephalogram (EEG) signals was purely visual, tedious, time-consuming, and required a physician. Changing this old approach to classification proves to be an extraordinary task that gained much

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9bbfdd18c86dda4d0d287cfbc4aa4bfe
http://www.sciencedirect.com/science/article/pii/S235291482100201X

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Classification of EEG signals for epileptic seizures detection and eye states identification using Jacobi polynomial transforms-based measures of complexity and least-square support vector machine

Autor: Daniel Tchiotsop, Laurent Chanel Djoufack Nkengfack, Romain Atangana, Didier Wolf, Valérie Louis-Door

Publikováno v: Informatics in Medicine Unlocked, Vol 23, Iss, Pp 100536-(2021)

Background and objectives Epilepsy is the most prevalent neurological disorder in humans which is characterized by recurrent seizures resulting in neurologic, cognitive, psychological and social consequences. In addition, the automatic identification

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::deb83921cc2a355bfff8141091207bf3
http://www.sciencedirect.com/science/article/pii/S2352914821000265

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Theoretical and numerical studies of gyrokinetic models for shaped Tokamak plasmas

Autor: Zoni, Edoardo

Gyrokinetics is a fundamental framework for the study of turbulence in magnetized fusion plasmas. In this thesis, we first propose a new methodology for the derivation of gyrokinetic models, based on polynomial transforms instead of Lie transforms. M

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::21553a64623fdcc27fa37cd50eb1e570
https://hdl.handle.net/21.11116/0000-0005-91C7-6

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Akademický článek

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Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

EEG signals analysis for epileptic seizures detection using polynomial transforms, linear discriminant analysis and support vector machines

Autor: Daniel Tchiotsop, Laurent Chanel Djoufack Nkengfack, Romain Atangana, Didier Wolf, Valérie Louis-Door

Publikováno v: Biomedical Signal Processing and Control
Biomedical Signal Processing and Control, Elsevier, 2020, 62, pp.102141. ⟨10.1016/j.bspc.2020.102141⟩

International audience; Electroencephalogram (EEG) signals are useful in understanding the human brain diseases like epilepsy which is characterized by an enduring predisposition to generate epileptic seizures and by neurologic, cognitive, psychologi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f328987dd31a0e7b2a117ccd1c179ae
https://doi.org/10.1016/j.bspc.2020.102141

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