| 基于L1-范数的最大间距准则 |
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| 引用本文： | 陈思宝,陈道然,罗斌.基于L1-范数的最大间距准则[J].电子学报,2016,44(6):1383-1388. |
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| 作者姓名： | 陈思宝 陈道然 罗斌 |
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| 作者单位： | 1. 安徽大学计算机科学与技术学院, 安徽合肥 230601;
2. 安徽省工业图像处理与分析重点实验室, 安徽合肥 230039 |
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| 基金项目： | 国家863计划项目(No．2014AA015104)；国家自然科学基金(No．61202228，No．61472002)；安徽省高校自然科学研究重点项目(No． KJ2012A004)；安徽省电力公司科技项目(521200130MOU，5212M01353B4) |
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| 摘 要： | 在进行线性投影降维时,由于传统的最大间距准则(Maximum Margin Criterion,MMC)算法基于L2-范数,易于受到野值(outliers)及噪声的影响.该文提出一种基于L1-范数的最大间距准则(L1-norm-based MMC,MMC-L1)降维方法,它充分利用L1-范数对野值及噪声的强鲁棒性以及最大间距准则,提出了一种快速迭代优化算法,并给出了其单调收敛到局部最优的证明.在多个图像数据库上的实验验证了该方法的鲁棒性与高效性.
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| 关 键 词： | 最大间距准则(MMC) L1-范数 线性投影 降维 |
| 收稿时间： | 2014-12-01 |
L1-Norm-Based Maxi mu m Margin Criterion |
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| CHEN Si-bao,CHEN Dao-ran,LUO Bin.L1-Norm-Based Maxi mu m Margin Criterion[J].Acta Electronica Sinica,2016,44(6):1383-1388. |
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| Authors: | CHEN Si-bao CHEN Dao-ran LUO Bin |
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| Affiliation: | 1. School of Computer Science and Technology, Anhui University, Hefei, Anhui 230601, China;
2. Key Laboratory for Industrial Image Processing and Analysis of Anhui Province, Hefei, Anhui 230039, China |
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| Abstract: | When performing dimensionality reduction with linear projections,maximum margin criterion (MMC)is often affected by outliers and noises due to L2-norm.In this paper,L1-norm-based maximum margin criterion (MMC-L1 ) is proposed for dimensionality reduction.It makes full use of Maximum Margin Criterion and strong robustness of L1-norm to outliers and noises.A rapid iterative optimization algorithm,with its proof of monotonic convergence to local optimum,is given.Experiments on several public image databases verify the robustness and efficiency of the proposed method. |
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| Keywords: | maximum margin criterion (MMC) L1-norm linear projection dimensionality reduction |
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