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Volumn 1, Issue , 2003, Pages 41-44

A kernel-based nonlinear discriminator with closed-form solution

Author keywords

[No Author keywords available]

Indexed keywords

CLOSED FORM SOLUTIONS; DISCRIMINANT CRITERIA; FEATURE SPACE; HANDWRITTEN DIGIT RECOGNITION; HIGHER-DIMENSIONAL; INPUT PATTERNS; KERNEL-BASED NONLINEAR DISCRIMINATORS; MEAN ENERGY; NONLINEAR FUNCTIONS; NONLINEAR SUPPORT VECTOR MACHINES; PATTERN CLASS; PATTERN CLASSIFICATION; PATTERN DISCRIMINATION; REPRODUCING KERNEL;

EID: 78650147592     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNNSP.2003.1279208     Document Type: Conference Paper
Times cited : (13)

References (13)
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  • 2
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  • 3
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  • 4
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    • Cortes, C.1    Vapnik, V.N.2
  • 6
    • 0035272287 scopus 로고    scopus 로고
    • An introduction to kernel-based learning algorithms
    • K. R. Müller, S. Mika, et al., "An Introduction to Kernel-based Learning Algorithms", IEEE Trans. Neural Networks, 12(2), pp.181-201, 2001.
    • (2001) IEEE Trans. Neural Networks , vol.12 , Issue.2 , pp. 181-201
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  • 7
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    • Generalized discriminant analysis using a kerne) approach
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  • 8
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    • Nonlinear fisher discriminant analysis using a minimum squared error cost function and the orthogonal least squares algorithm
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  • 9
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  • 10
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.