In numerous signal processing applications, non-stationary signals should be segmented to
piece-wise stationary epochs before being further analyzed. In this article, an enhanced …

Automatic segmentation of non-stationary signals such as electroencephalogram (EEG),
electrocardiogram (ECG) and brightness of galactic objects has many applications. In this …

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 …

While developing models of brain functioning by using time series data, the stationary
interval of the time series should be used to model the corresponding state of the brain. Here …

In bioinformatics, the biological functions of proteins and their interactions can often be
analyzed by the similarity of their sequences. In this paper, the authors combine the fractal …

Vehicle classification has a prominent role in intelligent transportation systems (ITS) for
traffic management and monitoring for various applications. One such application is the …

Inductive loop detectors (ILDs) are one of the most widely deployed traffic sensors. At
present, for lane-by-lane detection, ILDs require separate connecting cables for each loop …

Results: The implementation of the proposed method not only achieves an outstanding
accuracy rate of 99.66%, but it also exhibits a linear time complexity, ensuring efficient …

Nonlinear analysis of EEG recordings allows detection of characteristics that would probably
be neglected by linear methods. This study aimed to determine a suitable epoch length for …

It is often needed to label electroencephalogram (EEG) signals by segments of similar
characteristics that are particularly meaningful to clinicians and for assessment by …