کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
407956 678238 2011 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An iterative algorithm for robust kernel principal component analysis
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
An iterative algorithm for robust kernel principal component analysis
چکیده انگلیسی

We introduce a technique to improve iterative kernel principal component analysis (KPCA) robust to outliers due to undesirable artifacts such as noises, alignment errors, or occlusion. The proposed iterative robust KPCA (rKPCA) links the iterative updating and robust estimation of principal directions. It inherits good properties from these two ideas for reducing the time complexity, space complexity, and the influence of these outliers on estimating the principal directions. In the asymptotic stability analysis, we also show that our iterative rKPCA converges to the weighted kernel principal kernel components from the batch rKPCA. Experimental results are presented to confirm that our iterative rKPCA achieves the robustness as well as time saving better than batch KPCA.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 74, Issue 18, November 2011, Pages 3921–3930
نویسندگان
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