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Proof of Convergence and Performance Analysis for Sparse Recovery via Zero-Point Attracting Projection., , and . IEEE Trans. Signal Process., 60 (8): 4081-4093 (2012)Maximum Likelihood Estimation From Sign Measurements With Sensing Matrix Perturbation., , , and . IEEE Trans. Signal Process., 62 (15): 3741-3753 (2014)Capturing the Sparsity for Massive MIMO Channel with Approximate Message Passing., , , , , and . CSPS, volume 571 of Lecture Notes in Electrical Engineering, page 214-222. Springer, (2019)Robust zero-point attraction least mean square algorithm on near sparse system identification., , and . IET Signal Process., 7 (3): 210-218 (2013)An Easy-to-Implement Framework of Fast Subspace Clustering For Big Data Sets., , and . ICASSP, page 3612-3616. IEEE, (2020)Robust Transmit Beamforming for Parameter Estimation Using Distributed Sensors., , , and . IEEE Commun. Lett., 20 (7): 1329-1332 (2016)On estimating the loss of signal-to-noise ratio in compressive sensing based systems., , and . ChinaSIP, page 54-57. IEEE, (2013)LMS algorithm with gradient descent filter length., , and . IEEE Signal Process. Lett., 11 (3): 305-307 (2004)On the Performance Bound of Sparse Estimation with Sensing Matrix Perturbation, , and . CoRR, (2012)Near-oracle Recovery Performance of Greedy Pursuits with Replacement against General Perturbations, and . CoRR, (2012)