基于鲁棒主成分分析的电离层电离图去噪

IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology Pub Date : 2012-05-19 DOI:10.1109/ICSAI.2012.6223432

S. Lang, Bo Zhao, Shun Wang, Xiaojun Liu, G. Fang

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引用次数: 4

摘要

为了消除电离层电离层图噪声，提出了一种鲁棒主成分分析(RPCA)预处理优化分析方法。通过对该方法的基本原理、有效性和仿真结果的理论分析，指出了该方法的可行性，并给出了一种求解该RPCA问题的实用算法——加速近端梯度法(APGp)。最后，通过仿真结果验证了该方法的可行性。

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Ionospheric ionogram denoising based on Robust Principal Component Analysis

This paper proposes a preprocess optimization analysis called Robust Principal Component Analysis (RPCA) to eliminate the noises of ionospheric ionograms. Through the theoretical analysis of the basic principle and validity of this method and simulation results, we point out the feasibility of this method and give a useful algorithm named accelerated proximal gradient method (APGp) to solve this RPCA problem. Finally, we verify the feasibility of this method by some simulation results.

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IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology

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