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RecordNumber
2
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Author
Yijiang Jin, Shaoping Ma
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Title of Article
A Neural-Network Dimension Reduction Method for Large-Set Pattern Classification
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Title Of Journal
Lecture Notes in Computer Science
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Publication Year
2000
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Volum
1948/2000
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Page
426-433
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Keywords
Dimension Reduction , Neural Network , Principal Components Analysis , Chinese Character Recognition
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Notes
براي دانلود و مشاهده مقاله به قسمت لينكهاي مرتبط مراجعه نماييد
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Abstract
High-dimensional data are often too complex to be classified. K-L transformation is an effective dimension reduction method. However its result is not satisfactory in large-set pattern classification. In this paper a novel nonlinear dimension reduction method is presented and analyzed. The transform is achieved through a multi-layer feed-forward neural network trained with K-L transformation result. Experimental results show that this method is more effective than K-L transformation being applied in large-set pattern classification such as Chinese character recognition.
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URL
http://www.springerlink.com/content/1kke84qttpbt43yn/,/DL/Data Entry/DataEntryForm/EnterDocInfo.aspx,/DL/Data Entry/NewEdit/Documents/Math_English_Electronic_Articles_EditDoc_925.aspx
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Link To Document :
