Analysis of Spectrum Occupancy Using Machine Learning Algorithms.
IEEE Transactions on Vehicular Technology(2016)
摘要
In this paper, we analyze the spectrum occupancy in cognitive radio networks (CRNs) using different machine learning techniques. Both supervised techniques [naive Bayesian classifier (NBC), decision trees (DT), support vector machine (SVM), linear regression (LR)] and unsupervised algorithms [hidden Markov model (HMM)] are studied to find the best technique with the highest classification accuracy...
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关键词
Hidden Markov models,Support vector machines,Time-frequency analysis,Silicon,Machine learning algorithms,Accuracy
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