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When the ship is damaged after weapon attack, it is necessary for commanders to recognise its unsinkability grade quickly. Through unsinkability classification, we can know whether the ship will sink or not and its sinking probability. The unsinkability classification is a N-class pattern recognition problem. The fuzzy support vector machine (FSVM) is used to distinguish a certain unsinkability grade...
In order to solve the problem of feature extraction in the gear fault pattern recognition, a method of feature extraction based on atomic decomposition was proposed. Signals are rapidly decomposed using matching pursuit with the constructed Gabor dictionary. The frequency parameters and respective correlation values of the selected atoms constitute the feature vector of signal. Binary Tree Support...
In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler...
Aiming at the online fault diagnoses, the texture features which are usually used in image processing are firstly applied in the early fault signal recognition problems. After the parameter R based on gray-level co-occurrence matrix is defined, the parameter R extraction method of texture features is presented. Then, the novel fault signal recognition algorithm based on the parameter R of the texture...
The pattern information (PI) method was reasonably modified and firstly introduced to the observation data processing of electromagnetic satellite in this paper. Taking the moderate-strong earthquakes as examples, the IAP data recorded by the France DEMETER electromagnetic satellite were systematically processed with the modified PI method. We can find that the variation in non-seismic regions and...
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