Corrigendum to “An adaptive regularized smoothed ℓ~0 norm algorithm for sparse signal recovery in noisy environments” (Signal Processing (2017) 135 (153-157)(S016516841730004X)(10.1016/j.sigpro.2017.01.004))

Chen Jinli; Zhou Yun; Jin Lin; Li Jiaqing; Zhu Yanping

首页> 外文期刊>Signal processing >Corrigendum to “An adaptive regularized smoothed ℓ~0 norm algorithm for sparse signal recovery in noisy environments” (Signal Processing (2017) 135 (153-157)(S016516841730004X)(10.1016/j.sigpro.2017.01.004))

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Corrigendum to “An adaptive regularized smoothed ℓ~0 norm algorithm for sparse signal recovery in noisy environments” (Signal Processing (2017) 135 (153-157)(S016516841730004X)(10.1016/j.sigpro.2017.01.004))

机译：“在噪声环境中稀疏信号恢复的自适应正则化平滑ℓ〜0范数算法”勘误（信号处理（2017）135（153-157）（S016516841730004X）（10.1016 / j.sigpro.2017.01.004））

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The authors regret making some mistakes in estimating the regularization parameter of the Eqs. (11) and (13), as well as Algorithm 1 and Algorithm 2.

机译：作者后悔在估计等式的正则化参数时犯了一些错误。（11）和（13），以及算法1和算法2。

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《Signal processing》 |2017年第12期|287-287|共1页
作者
Chen Jinli; Zhou Yun; Jin Lin; Li Jiaqing; Zhu Yanping;
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Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China,School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China;

School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China;

Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China,Nanjing Research Institute of Electronics Technology, Nanjing, China;

Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China,School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China;

School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China;

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1. An adaptive regularized smoothed ℓ° norm algorithm for sparse signal recovery in noisy environments [J] . Jinli Chen, Yun Zhou, Lin Jin, Signal processing . 2017,第juna期

机译：噪声环境下稀疏信号恢复的自适应正则平滑ℓ°范数算法
2. Corrigendum to ‘Dynamic Recovery for Block Sparse Signals’ (Signal Processing (2016) 130 (197-203) (S0165168416301384) (10.1016/j.sigpro.2016.06.027)) [J] . Ren Junying, Wei Chen, Yu Lei, Signal processing . 2017,第deca期

机译：“块稀疏信号的动态恢复”勘误表（信号处理（2016）130（197-203）（S0165168416301384）（10.1016 / j.sigpro.2016.06.027））
3. Corrigendum to "On the application of a unified adaptive filter theory in the performance prediction of adaptive filter algorithms" [Digital Signal Process. 19 (2009) 410-432] (DOI:10.1016/j.dsp.2008.10.002) [J] . Abadi M.S.E., Hus?y J.H. Digital Signal Processing . 2010,第1期

机译：更正为“关于统一自适应滤波器理论在自适应滤波器算法性能预测中的应用” [数字信号处理。 19（2009）410-432]（DOI：10.1016 / j.dsp.2008.10.002）
4. Anti-noise-folding regularized subspace pursuit recovery algorithm for noisy sparse signals [C] . Xianjun Yang, Qimei Cui, Dutkiewicz E., IEEE Wireless Communications and Networking Conference . 2014

机译：噪声稀疏信号的抗噪折叠正则子空间跟踪恢复算法
5. Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization. [D] . Parekh, Ankit. 2016

机译：绕过L1正则化的限制：使用非凸正则化的凸稀疏信号处理。
6. Sparsity Adaptive Matching Pursuit Detection Algorithm Based on Compressed Sensing for Radar Signals [O] . Yanbo Wei, Zhizhong Lu, Gannan Yuan, 2017

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7. Anti-noise-folding regularized subspace pursuit recovery algorithm for noisy sparse signals [O] . Yang, Xianjun, Cui, Qimei, Dutkiewicz, Eryk, 2014

机译：噪声稀疏信号的抗噪折叠正则子空间跟踪恢复算法

Corrigendum to “An adaptive regularized smoothed ℓ~0 norm algorithm for sparse signal recovery in noisy environments” (Signal Processing (2017) 135 (153-157)(S016516841730004X)(10.1016/j.sigpro.2017.01.004))

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