Methods of EEG Signal Features Extraction Using Linear Analysis in Frequency and Time-Frequency Domains

Methods of EEG Signal Features Extraction Using Linear Analysis in Frequency and Time-Frequency Domains

Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the comp...

A Time-Frequency approach for EEG signal segmentation

The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...

Newborn EEG connectivity analysis using time-frequency signal processing techniques

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Analysis of the Vibration Signal Using Time-frequency Methods

Condition monitoring (CM) is an essential technique used for monitoring various systems and system components and is supplemented with other techniques, such as video monitoring. Due to the fact that the acceleration signal is suitable for acquisition and is of non-stationary nature, CM is used to monitor various parameters of a monitored system. In order to process the acquired vibration signa...

Signal Analysis by Time-Frequency Methods