Since the operative definition given by CWJ Granger of an idea expressed by N. Wiener, the
Wiener-Granger causality (WGC) has been one of the most relevant concepts exploited by …

Orthogonal regression is one of the prominent approaches for linear regression used to
adjust the estimate of predictor errors. It can be considered as a least square regression with …

Detecting epileptic seizures in electroencephalography (EEG) signals is a challenging task
due to nonstationary processes of brain activities. Currently, the epilepsy is mainly detected …

Conventional methods for the structural nondestructive testing (NDT) such as pulsed eddy
current (PEC), ultrasonic detection (UT), and so on are based on the output signal …

The electroencephalogram (EEG) signal analysis is a valuable tool in the evaluation of
neurological disorders, which is commonly used for the diagnosis of epileptic seizures. This …

An efficient multiwavelet-based time-varying modeling scheme is proposed for time–
frequency analysis (TFA) of electroencephalogram (EEG) data. In the new multiwavelet …

Model structure selection plays a key role in non-linear system identification. The first step in
non-linear system identification is to determine which model terms should be included in the …

Severe geomagnetic disturbances can be hazardous for modern technological systems. The
reliable forecast of parameters related to the state of the magnetosphere can facilitate the …

A new parametric approach is proposed for nonlinear and nonstationary system
identification based on a time-varying nonlinear autoregressive with exogenous input (TV …

This paper introduces a new method to improve the reliability and confidence level of defect
depth measurement based on pulsed thermographic inspection by addressing the over …