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Data Stream mining (DSM) is claimed to be the successor of traditional data mining where it is capable of mining continuous incoming data streams in real-time with an acceptable performance. Nowadays many computer applications evolved to online and on-demand basis, fresh data are feeding in at high speeds. Not only a decision response needs to be made rapidly, the trained decision tree models would...
Sparse over complete representations have attracted much interest recently for their applications to signal processing. In a recent work, Donoho, Elad, and Temlyakov (2006) showed that, assuming sufficient sparsity of the ideal underlying signal and approximate orthogonality of the over complete dictionary, the sparsest representation can be found, at least approximately if not exactly, by either...
In this presentation, a new algorithm for multi-user spectrum management is introduced - based on a greedy algorithm with new heuristic adjustments. The new algorithm is tested for two scenarios and is proved to achieve an excellent performance. Computational complexity is low, making it tractable for spectrum balancing in large bundles.
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