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Hyperspectral image denoising is an important preprocessing step in the analysis of hyperspectral images in several applicaitons domains. These images often gets corrupted by various kinds of noise during acquisition process. There are several studies on reducing Gaussian noise from hyperspectral images. This work addresses the problem of reducing mixed noise from hyperspectral images; in particular...
Power quality (PQ) is one of the most significant issues in power monitoring systems and smart grids in recent years. Identifying disturbances has an important role in improving PQ. The intention of this paper is to improve the accuracy of the detection step in PQ disturbances. To do so an adaptive method called CEEMD (complete ensemble empirical mode decomposition) is used here for the first time...
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