Abstract
SCoSaMP (Signal space-based CoSaMP) is an algorithm with excellent performance proposed for reconstruct signals acquired with Sub-Nyquist sampling system based on redundant Gabor frames. However, there’s still no estimation of the lower bound of the error MSE under Gaussian noise and it is hard to estimate the reconstruction performance of SCoSaMP algorithm from a theoretical point of view. This paper presents the CRLB (Cramér–Rao Low Bound) estimation for MSE (Mean Square Estimate) of SCoSaMP algorithm and analyzes the impact factor for noise suppressing, which shows the road for further improving the algorithm.
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Acknowledgement
The authors thank an anonymous reviewer for useful suggestions that helped improve the presentation and Mechanical Engineering College who funded my research by the National Natural Science Foundation of China (Grant No. 61501493).
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Wang, C., Chen, P., Yang, H., Li, W., Liu, D., Meng, C. (2019). Cramér–Rao Low Bound Estimation for MSE of SCoSaMP Algorithm. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_263
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DOI: https://doi.org/10.1007/978-981-10-6571-2_263
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