کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533767 870166 2008 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Perturbation scheme for online learning of features: Incremental principal component analysis
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Perturbation scheme for online learning of features: Incremental principal component analysis
چکیده انگلیسی

A new incremental online feature extraction approach is proposed based on principal component analysis in conjunction with perturbation theory which for its validity requires the perturbation parameter to be small. Our approach is found to be computationally more efficient in comparison to batch method which for its applicability requires simultaneous availability of all observations for computation of features. It is found on the basis of numerical experiments that the results based on our approach besides being in good agreement with the batch method and other incremental methods are also computationally more efficient. To demonstrate the efficacy of the proposed scheme, experiments have been performed on randomly generated datasets as well as on low and high dimensional datasets, i.e. UCI and face datasets which are available in public domain.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 41, Issue 5, May 2008, Pages 1452–1460
نویسندگان
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