Journal
ARTIFICIAL INTELLIGENCE REVIEW
Volume 37, Issue 3, Pages 169-180Publisher
SPRINGER
DOI: 10.1007/s10462-011-9225-y
Keywords
Pattern recognition; Feature extraction; Neural networks; Independent component analysis; Manifold learning
Categories
Funding
- Natural Science Foundation of Jiangsu Province of China [BK2009093]
- National Nature Science Foundation of China [60975039, 41074003]
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In research of pattern recognition, we always want to achieve the correct classification rate according to the characteristics required. Feature extraction greatly affects the design and performance of the classifier, and it is one of the core issue of PR research. As an important component of pattern recognition, feature extraction has been paid close attention by many scholars, and currently has become one of the research hot spots in the field of pattern recognition. This article gives a general discussion of feature extraction, includes linear feature extraction and nonlinear feature extraction, and introduces the frontier methods of this field, at last discusses the development tendency of feature extraction.
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