In this study, it has been intended to analyze Electroencephalography (EEG) signals by
Wavelet Transform (WT) for diagnosis of epilepsy, to employ various Artificial Neural …

In this study, it has been intended to perform an automatic classification of
Electroencephalography (EEG) signals via Artificial Neural Networks (ANN) and to …

Epilepsy is a common neurological disorder characterized by the recurrence of seizures,
which can significantly impact the lives of patients. Electroencephalography (EEG) can …

Electroencephalogram (EEG) is a diagnostic method that provides information about the
functioning of the brain. EEG can be used to diagnose the abnormally functioning part of the …

The aim of this study is to diagnose epileptic seizures by using different machine learning
algorithms. For this purpose, the frequency components of the EEG are extracted by using …

Since EEG is one of the most important sources of information in therapy of epilepsy, several
researchers tried to address the issue of decision support for such a data. In this paper, we …

Epileptic seizures are the outcome of the transient and the sudden electrical disorder of the
brain. The Electroencephalogram (EEG) is a diagnostic imaging method, which measures …

Electroencephalogram (EEG) has established itself as an important means of identifying and
analyzing epileptic seizure activity in humans. In most cases, identification of the epileptic …

The uncertainty in human brain leads to the formation of epilepsy disease in human. The
automatic detection and severity analysis of epilepsy disease is proposed in this article …

In this work, we proposed a versatile signal processing and analysis framework for
Electroencephalogram (EEG). Within this framework the signals were decomposed into the …