Nonlinear feature extraction based on centroids and kernel functions
نویسندگان
چکیده
منابع مشابه
Nonlinear feature extraction based on centroids and kernel functions
A nonlinear feature extraction method is presented which can reduce the data dimension down to the number of clusters, providing dramatic savings in computational costs. The dimension reducing nonlinear transformation is obtained by implicitly mapping the input data into a feature space using a kernel function, and then finding a linear mapping based on an orthonormal basis of centroids in the ...
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Feature Extraction (FE) techniques are widely used in many applications to pre-process data in order to reduce the complexity of subsequent processes. A group of Kernel-based nonlinear FE ( H E ) algorithms has attracted much attention due to their high per$ormance. However, a serious limitation that is inherent in these algorithms -the maximal number of features extracted by them is limited by...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2004
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2003.07.011