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Kernel principal component analysis (KPCA) has been a state-of-the-art nonlinear process monitoring method. However, KPCA assumes the single operation mode while the real industrial processes often run under multiple operation conditions. In order to monitor the nonlinear multimode processes effectively, this paper proposes a modified KPCA method assisted by the local statistical analysis, referred...
It is a difficult problem that targets are detected in nature background, especially in images corrupted by noise. In order to solve this problem, a method based on feature salience is proposed for targets automatic detection in nature background. Firstly, an adaptive wavelet thresholding method is used to denoise for noisy target images. Then minimum probability of error was been used to build to...
Radar emitter recognition plays an important role in military automated command and control system. It is a composite task that involves radar signal interception, modulation recognition, features extraction and classification. In this paper, a wavelet packet transform is used for feature extraction of unintentional modulation on pulse (UMOP). Then specific radar emitter recognition is achieved by...
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