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Data collection is a crucial operation in wireless sensor networks. The design of data collection schemes is challengingdue to the limited energy supply and the hot spot problem. Leveraging empirical observations that sensory data possess strongspatiotemporal compressibility, this paper proposes a novel compressive data collection scheme for wireless sensor networks. We adopt a power-law decaying...
In this paper, we propose a novel approach SDR-CS (Sparse Dimensionality Reduction based on CS) based on compressed sensing to reduce dimensionality. With certain constraint of objective function, our semi-supervised learning method utilizes instance to construct the optimally sparse dictionary in the training dataset, employs K-SVD and OMP algorithms to improve the convergence rate of learning, and...
The paper proposes a method of schistosoma cercariae image recognition via sparse representation(IRSR). In the method, all the schistosoma cercariae image training samples compose the dictionary for sparse representation. For each test sample, its projection coefficient in the dictionary is computed and the category which has minimal residual value is assigned to it. We also investigate the effect...
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