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Compressed sensing (CS) is on recovery of high dimensional signals from their low dimensional linear measurements under a sparsity prior and digital quantization of the measurement data is inevitable in practical implementation of CS algorithms.
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2012
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J. Laska and R. Baraniuk, “Regime change: Bit-depth versus measurement-rate in compressive sensing,” IEEE Transactions on Signal Processing , vol. 60, no. 7, pp. 3496–3505, 2012
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A. Maleki, L. Anitori, Z. Yang, and R. Baraniuk, “Asymptotic analysis of complex LASSO via complex approximate message passing (CAMP),” IEEE Transactions on Information Theory, DOI: 10.1109/TIT.2013.2252232 , 2013
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Z. Yang, L. Xie, and C. Zhang, “Off-grid direction of arrival estimation using sparse Bayesian inference,” IEEE Transactions on Signal Processing , vol. 61, no. 1, pp. 38–43, 2013
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