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In the paper, we study how the theory of compressed sensing is applied in wireless sensor networks to capture sparse signals of interest. Traditional data collection and compressive data gathering separately use client/server paradigm and dense random matrix, leading high computation load and energy consumption. We adopt sparse binary matrix for the measurement matrix. A mobile agent based compressed...
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