.png){kind=icon}
返回
Greedy method for robust linear regression
.png){kind=icon}
OA
AI
DOI：10.1016/j.neucom.2017.03.010.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we propose a greedy method to estimate the unknown vector from linear observation with sparse noise. We prove that the algorithm can reconstruct the vector provided the sampling matrix satisfies certain condition and the noise is sparse. We also prove that such a condition holds with high probability for random matrix if its scale satisfies certain assumption. Numerical results are provided to demonstrate the efficiency of the algorithm. And we also consider using the algorithm for salt&pepper noise removal in signal processing. (C) 2017 Elsevier B.V. All rights reserved.
Keyword:
Greedy method
Robust linear regression
Sparse noise
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
.png){kind=icon}
AN EFFICIENT TVL1 ALGORITHM FOR DEBLURRING MULTICHANNEL IMAGES CORRUPTED BY IMPULSIVE NOISE一种有效的TVL1算法，用于对脉冲噪声破坏的多通道图像进行去模糊
PREAI
分享收藏
查看更多内容