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Optoacoustic spectroscopy detection is one of the newest detection methods. It can detect the weak-absorbed specimen with high-sensitivity. In this treatise, the technique is applied to detect the water quantity in oil. There are two spectral absorbing wave bands of water, so the innovation of this project lies in adopting laser sources with two different wave bands. This can effectively strengthen...
Original signal is decomposed by wavelet in different scales, the wavelet decomposition coefficients of the real signal are held, and the wavelet decomposition coefficients of the noise are eliminated, then the signal is reconstructed by inverse wavelet transform. Kernel PCA can eliminate the relativity of variables and extract the fault information better, the feature information of the pretreatment...
Drainpipe ultrasonic non-destructive testing is liable to be interfered with the external environment. So it is important to remove the noise signal effectively in drainpipe ultrasonic non-destructive testing. The testing system is constructed by self-adaptive wavelet neural networks which is using the wavelet and neural network algorithm. Better fitting signal is achieved by choosing Orthogonal Daubechies...
In this study, a brain-computer interface (BCI) using electrocorticograms (ECoG) is proposed. Feature extraction is an important task that significantly affects the classification results. First, the discrete wavelet transform was applied to ECoG signals from one subject performing imagined movements of either the left small-finger or the tongue. After preprocessing, relative wavelet energy of selected...
It is important to remove the noise signal effectively in non-destructive testing. Using the wavelet and neural network algorithm, the author constructed self-adaptive wavelet neural networks in the ultrasonic testing. Better fitting signal is achieved by choosing Orthogonal Daubechies wavelet neuron and optimized scale parameter. The simulation results showed less distortion and better noise cancellation,...
Using principal component analysis and wavelet analysis technology, an improved PCA method is proposed in order to detect industrial faults. The definition of the differences between principal component subspaces is introduced. The program structure of the system is set up based on the improved method. The simulation result shows that the improved PCA has better performance; and gives an efficient...
The classification problem of small target is a very significant but challenging task in the field of automatic target recognition. In this paper, an enhanced support vector machine with the wavelet kernel function was proposed. In order to concentrate on the classification, It is assumed that regions containing possible targets are provided. Then the Hu's moment invariants are chosen as the feature...
Computer-aided detection (CAD) schemes can assist radiologists in the early detection of lung cancer which is crucial to the chance for curative treatment. Characterizing the pulmonary nodules in the multislice X-ray computed tomography (CT) images is notoriously difficult. This is due to the fact that the anatomical structures such as blood vessels, bronchi, and alveoli are subject to partial volume...
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