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    A comprehensive analysis of support vector machine and Gaussian mixture model for classification of epilepsy from EEG signals

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    values and accuracy. The best result is obtained with an accuracy of 97.84% when FMI is used as a dimensionality reduction technique and followed ...

    Non linear ICA and logistic regression for classification of epilepsy from EEG signals

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    patients may not be aware of it and so it increases the risk of physical injury. Due to the disturbed brain activity, epileptic seizures are caused ...

    Optimization of fuzzy outputs for classification of epilepsy from EEG signals using linear discriminant analysis

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    delay of 2.124 and an average performance index of about 91.9215% is obtained. ...

    Metric multidimensional scaling and aggregation operators for classifying epilepsy from EEG signals

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    As a result of sudden and excessive electrical discharges in a specific group of brain cells called neurons, epilepsy occurs and is usually ...

    Hilbert transform with Elman backpropagation and multilayer perceptrons for epilepsy classification

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    hazardous consequences to the patients. The recordings of the EEG are quite long and so with the help of Hilbert Transform the dimensions of the EEG ...

    Power spectral density and KNN based adaboost classifier for epilepsy classification from EEG

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    In the arena of biomedical engineering, the classification and analysis of epilepsy from Electroencephalography (EEG) signals forms an ...

    Sparse PCA and soft decision tree classifiers for epilepsy classification from EEG signals

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    neurons in the brain is seizures which limits the mental and physical activities of the patient. To measure the electrical potential from the ...

    Epilepsy classification through multi-label dimensionality reduction through dependence maximization and elite genetic algorithm

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    neurological disorder that exists since a long period of time. Characterized by continuous, spontaneous and recurrent seizures, they cause a great harm ...

    Modified expectation maximization based sparse representation classifier for classification of epilepsy from EEG signals

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    to a lot of temporary changes in behaviour, perception, movement and health. Epilepsy occurs due to the rapid firing of neurons in the ...

    Expectation maximization based logistic regression for breast cancer classification

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017
    In the field of data mining and computational intelligence, many researchers have developed a lot of feasible solutions for the breast ...

    Factor Analysis and Weighted KNN Classifier for Epilepsy Classification from EEG signals

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2018
    Many people suffering from epilepsy can be controlled with the help of anti -epileptic drugs. For some people remission is possible and for ...

    Multilayer Autoencoders and EM - PCA with Genetic Algorithm for Epilepsy Classification from EEG

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2018
    in the electrical activities of the brain cells, seizures occur and it gives rise to many abnormal behaviors like unusual perceptions ...