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By exploiting the sparsity of mode shapes, CS can also enable efficient spatial reconstruction using fewer spatially distributed sensors.
Inspired by that technique, we devised a simple method that encodes temporal information into the spatial domain by exploiting the sparsity of single-molecule samples similar to spatially encoding a spectrum7 or an axial position of single molecules8.
Further, by exploiting the sparsity pattern exhibited by the problem, we show that the original POP can be equivalently reformulated as an SDP problem with a rank-1 constraint.
By exploiting the sparsity and symmetry, the size of the problem beyond which FIND is faster than other methods typically decreases from a 130 × 130 2D mesh down to a 40 × 40 mesh.
By exploiting the sparsity profile, the CS-based CFO estimation is presented in [8, 9] for multi-user uplink.
Aviyente proposed a compressed sensing framework for EEG compression by exploiting the sparsity of EEG signals in a Gabor frame [11].
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Furthermore, the proposed technique can be enhanced by thresholding the CIR to a certain value and also by exploiting the common sparsity feature inherent in the system channel.
Recently, compressive sensing and sparse reconstruction methods become attractive in DOA estimation by exploiting the spatial sparsity of the signal arrivals (e.g., [5 8]).
Exploiting the sparsity of source DOAs in the whole angular region, we propose a novel DOA tracking method to estimate the source locations and trace their trajectories by using the variational sparse Bayesian learning (VSBL) embedded with Kalman filter (KF).
The second stage is a BSS algorithm exploiting the sparsity of the sources in the time-frequency domain.
By exploiting the channel spatial sparsity, massive MIMO channel is compressed in the beam-domain under certain selected basis spaces and as a result the channel dimension required to be estimated can be greatly reduced.
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