9786202815055 - performance analysis of epilepsy risk level from eeg signals di r., deepa; c., ganesh babu; r., harikumar (9 risultati)
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Performance Analysis of Epilepsy Risk Level From EEG Signals | Deepa R. (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202815055 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter:… preigu.
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Book describes the epilepsy disorder and it is characterized by the existence of abnormal synchronous discharges in large ensembles of neurons in brain structures. These discharges appear either during seizures (interictal per…iods) or between seizures (interictal periods). Epileptic seizures are manifestations of epilepsy, which are recorded using the EEG. The objective of this work is to classify the risk level of Epileptic EEG using HMM. The dimensionality reduction of signal is done using various modules like Singular value Decomposition and vector quantization. Each of this method has its own methodology of data decomposition. Training sequence from the dimensionally reduced data is finally classified by the HMM. The HMM is used to classify the risk levels of epilepsy based on extracted parameters from EEG signals of the patient. 52 pp. Englisch.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: R. DeepaDr. R. Deepa, Assistant Professor (Level III), EIE Department, Bannari Amman Institute of Technology, Sathyamangalam.This Book describes the epilepsy disorder and it is characterized by the exi…stence of abnormal synchrono.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This Book describes the epilepsy disorder and it is characterized by the existence of abnormal synchronous discharges in large ensembles of neurons in brain structures. These discharges appear either during seizures (interictal periods…) or between seizures (interictal periods). Epileptic seizures are manifestations of epilepsy, which are recorded using the EEG. The objective of this work is to classify the risk level of Epileptic EEG using HMM. The dimensionality reduction of signal is done using various modules like Singular value Decomposition and vector quantization. Each of this method has its own methodology of data decomposition. Training sequence from the dimensionally reduced data is finally classified by the HMM. The HMM is used to classify the risk levels of epilepsy based on extracted parameters from EEG signals of the patient.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Book describes the epilepsy disorder and it is characterized by the existence of abnormal synchronous discharges in large ensembles of neurons in brain structures. These discharges appear either during seizures (interictal periods)… or between seizures (interictal periods). Epileptic seizures are manifestations of epilepsy, which are recorded using the EEG. The objective of this work is to classify the risk level of Epileptic EEG using HMM. The dimensionality reduction of signal is done using various modules like Singular value Decomposition and vector quantization. Each of this method has its own methodology of data decomposition. Training sequence from the dimensionally reduced data is finally classified by the HMM. The HMM is used to classify the risk levels of epilepsy based on extracted parameters from EEG signals of the patient.
