Objective: Exploring resting-state functional networks using functional magnetic resonance imaging (fMRI) is a hot topic in the field of brain functions. Previous studies suggested that the frequency dependence between blood oxygen level dependent (BOLD) signals may convey meaningful information regarding interactions between brain regions. Methods: In this article, we introduced a novel freque...

Objective. This research provides objective and quantitative parameters of the traditional Chinese medicine (TCM) pulse conditions for distinguishing between patients with the coronary heart disease (CHD) and normal people by using the proposed classification approach based on Hilbert-Huang transform (HHT) and random forest. Methods. The energy and the sample entropy features were extracted by ...

For non-destructive evaluation (NDE) of concrete, efficient and accurate imaging techniques are needed for a reliable evaluation of safety and serviceability of structures. Imaging of concrete structures is considered a very challenging task since it is a non-homogeneous material. In this paper, the acoustic (stress wave) technique was applied by using Ultrasonics and Synthetic Aperture Focusin...

Existing studies have attempted to determine the tool chipping condition using indirect method of data capture and intelligent analysis techniques considering machine parameters, conditions signal processing techniques. Due obstructive nature machining operation, however, it is daunting use capturing intelligently as well that workpiece. This study aimed apply some advanced vibration signals ca...

Phase interactions among signals of physical and physiological systems can provide useful information about the underlying control mechanisms of the systems. Physical and biological recordings are often noisy and exhibit nonstationarities that can affect the estimation of phase interactions. We systematically studied effects of nonstationarities on two phase analyses including (i) the widely us...

The aim of this paper is to develop an automated system for epileptic seizure prediction from intracranial EEG signals based on Hilbert-Huang transform (HHT) and Bayesian classifiers. Proposed system includes decomposition of the signals into intrinsic mode functions for obtaining features and use of Bayesian networks with correlation based feature selection for binary classification of preicta...

Hilbert-Huang transform (HHT) is a novel signal processing method which can efficiently handle nonstationary and nonlinear signals. It contains two key parts: Empirical Mode Decomposition (EMD) and Hilbert transform. EMD decomposes signals into a complete series of Intrinsic Mode Functions (IMFs), which capture the intrinsic frequency components of original signals. Hilbert transform is adopted...

Identifying the different damage modes of wood is great significance for monitoring occurrence, development, and evolution material damage. This paper presents research results application acoustic emission (AE) technology to analyze evaluate mapping relationship between pattern in fracture process AE signal. For three-point bending specimen with pre-crack, double cantilever beam specimen, sing...

Vibration problems in rotors can be extremely frustrating and may lead to greatly reduced reliability. By utilizing the proper data collection and analysis techniques, the faults because of vibration can be discovered and predicted. The signal analysis is important in extracting fault characteristics in fault diagnosis of machinery. The traditional signal analysis can not settle for non-station...

Due to the increased integration of distributed generations in networks, their development and operation are facing protection challenges that traditional systems incapable addressing. These problems include variations fault current during various modes, diverse network topology, high impedance faults. Therefore, appropriate reasonable detection is highly encouraged improve dependability networ...