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基于L1-范數(shù)的二維線性判別分析

陳思寶 陳道然 羅斌

陳思寶, 陳道然, 羅斌. 基于L1-范數(shù)的二維線性判別分析[J]. 電子與信息學(xué)報(bào), 2015, 37(6): 1372-1377. doi: 10.11999/JEIT141093
引用本文: 陳思寶, 陳道然, 羅斌. 基于L1-范數(shù)的二維線性判別分析[J]. 電子與信息學(xué)報(bào), 2015, 37(6): 1372-1377. doi: 10.11999/JEIT141093
Chen Si-bao, Chen Dao-ran, Luo Bin. L1-norm Based Two-dimensional Linear Discriminant Analysis[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1372-1377. doi: 10.11999/JEIT141093
Citation: Chen Si-bao, Chen Dao-ran, Luo Bin. L1-norm Based Two-dimensional Linear Discriminant Analysis[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1372-1377. doi: 10.11999/JEIT141093

基于L1-范數(shù)的二維線性判別分析

doi: 10.11999/JEIT141093
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61202228)和安徽省高校自然科學(xué)研究重點(diǎn)項(xiàng)目(KJ2012A004)資助課題

L1-norm Based Two-dimensional Linear Discriminant Analysis

  • 摘要: 為了避免圖像數(shù)據(jù)向量化后的維數(shù)災(zāi)難問(wèn)題,以及增強(qiáng)對(duì)野值(outliers)及噪聲的魯棒性,該文提出一種基于L1-范數(shù)的2維線性判別分析(L1-norm-based Two-Dimensional Linear Discriminant Analysis, 2DLDA-L1)降維方法。它充分利用L1-范數(shù)對(duì)野值及噪聲的強(qiáng)魯棒性,并且直接在圖像矩陣上進(jìn)行投影降維。該文還提出一種快速迭代優(yōu)化算法,并給出了其單調(diào)收斂到局部最優(yōu)的證明。在多個(gè)圖像數(shù)據(jù)庫(kù)上的實(shí)驗(yàn)驗(yàn)證了該方法的魯棒性與高效性。
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出版歷程
  • 收稿日期:  2014-08-18
  • 修回日期:  2015-02-04
  • 刊出日期:  2015-06-19

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