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In this paper, we consider the problem of unsupervised feature selection. Recently, spectral feature selection algorithms, which leverage both graph Laplacian and spectral regression, have received increasing attention. However, existing spectral feature selection algorithms suffer from two major problems: 1) since the graph Laplacian is constructed from the original feature space, noisy and irrelevant...
This paper addresses the problem of joint optimization of subchannel selection and spectrum sensing time for multiband cognitive radio networks. In particular, we construct a multiband spectrum sensing framework, and derive the probabilities of detection and false alarm taking the different subchannel gain into account. Furthermore, we formulate the multiband sensing as a two-parameter optimization...
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