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2019 | OriginalPaper | Chapter

Cramér–Rao Low Bound Estimation for MSE of SCoSaMP Algorithm

Authors : Cheng Wang, Peng Chen, Huahui Yang, Wanling Li, Deliang Liu, Chen Meng

Published in: Communications, Signal Processing, and Systems

Publisher: Springer Singapore

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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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Metadata
Title
Cramér–Rao Low Bound Estimation for MSE of SCoSaMP Algorithm
Authors
Cheng Wang
Peng Chen
Huahui Yang
Wanling Li
Deliang Liu
Chen Meng
Copyright Year
2019
Publisher
Springer Singapore
Book
Communications, Signal Processing, and Systems

Print ISBN: 978-981-10-6570-5

Electronic ISBN: 978-981-10-6571-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-10-6571-2_263