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In this paper, we examine the sparsity-based time-frequency signal representation (TFSR) of randomly thinned nonstationary signals in a multi-sensor platform to yield improved performance with reduced number of samples in each sensor. The property that different sensors share identical auto-term time-frequency regions renders the TFSR a group sparse reconstruction problem, which is effectively solved...
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