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Motor is a kind of imperative driving device, whether a motor can monitor its state precisely and diagnose fault timely have a profound impact. This paper mainly investigates the improvement of the general method of motor defect diagnosis to achieve higher accuracy. Unfortunately, every classifier has their own respective advantages and disadvantages, using the typical machine learning methods separately...
A novel deep learning classification method for hyperspectral data based on convolutional neural network is proposed in this paper. Deep learning means bringing multiple layers instead of one to the structure. Through convolution layers and pooling layers, the features in different layers are extracted from original spectral feature images. The key of this method is to restructure spectral feature...
To address the multi-classification problems of hyperspectral dataset, a new method with weighted kernel function based on Chernoff distance is proposed. Chernoff distance utilizes the information between categories and strengthens the separability of original dataset. The adjustable parameter in Chernoff distance can fit the hyperspectral dataset well compared with other least upper bounds. Pairwise...
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