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The paper presents an on-line brain-computer interface (BCI) based on visual evoked potential (VEP) P300. The BCI is applied to control a multi-DOF manipulator. This BCI system includes five modules which are visual stimulator, signal acquisition, data processing, communication and motion control of manipulator. Stimulation program and experimental scheme are designed based on LabVIEW platform and...
The paper has extracted the energy spectrum entropy of wavelet packet as the eigen vector of fault patterns, through analyzing the vibration signal in the decomposition of wavelet packet when Low-Voltage (LV) Circuit Breaker broke down. Based on the concept of Clustering Center, a Naïve Bayesian classifier has been constructed. By using the weight of probability measure, the correlations between...
A Brain-Computer Interface (BCI) system based on Steady State Visual Evoked Potentials (SSVEP) was presented in this paper to realize four-direction motion control of a small ball on the computer screen. The system mainly included five parts of visual stimulator, electroencephalogram (EEG) amplifier, EEG acquisition, EEG processing and machine human interface on the computer screen. The system utilized...
The research designed a brain-computer interface (BCI) system based on the steady state VEP potential (SSVEP). It used the wavelet packet decomposition technology to extract feature. Comparing with the FFT, this method could avoid the spectrum leakage and improve the information transmission rate. A SSVEP-based controlling system of multi-DoF manipulator was presented in this paper on the basis of...
Acoustic emission (AE) is a new approach to rub-impact recognition. The fuzzy entropy is introduced to analyze the effectiveness of the features, and the method of fuzzy comprehensive evaluation combining effectiveness analysis is proposed to acoustic emission recognition. Duration, average amplitude, maximum amplitude, dynamic range of amplitude and the first four nodes energies of the reconstructing...
An on-line BCI system is designed to control self-designed robot for photo-taking. The simulated experiment of BCI's application outside space-ship in aerospace is included in this paper. The P300-based BCI system includes three modules: visual stimulus, EEG sampling and signal processing, external robot controlling. A robot acts as the carrier for the camera. The robot is developed with the ability...
In the research of brain and cognitive science, the key problem of analyzing functional Magnetic Resonance Imaging (fMRI) data is not only to detect and locate the functional active signal accurately but also to obtain the dynamic changes of activated areas. This paper represents a novel approach to decompose the time series data in activated areas based on wavelet analysis for fMRI data processing;...
An efficient denoising procedure for magnetic resonance imaging is presented. It is well known that the noise in magnetic resonance imaging has a Rician distribution. Unlike additive Gaussian noise, Rician noise is signal dependent, and separating signal from noise is a difficult task. This paper presents an iterative method based on wavelet shrinkage for Rician noise removal. Experiments show that...
The wavelet entropy (WE), a new quantity is introduced to describe the time-frequency character of an atomic clock. It can be obtained through synthesizing wavelet coefficients based on energy partition. We connected the Allan variance with the wavelet entropy, and used the WE to character the stability of a clock. The performance of the approach was examined by real data and the results demonstrated...
Because of excellent capability of description of local texture, local binary patterns (LBP) have been applied in many areas. In this paper, we enhance the classical LBP method from three aspects for facial expression recognition: image data, extracting features and the way of combining all these features. At first, we adopt wavelet to decomposed images into four kinds of frequency images from which...
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