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Volumn , Issue , 2008, Pages 180-184

Feature extraction via kernelized signal fraction analysis vs kernelized principal component analysis

Author keywords

Kernel principal component analysis; Kernel signal fraction analysis; Noise reduction

Indexed keywords

ENHANCED PERFORMANCE; KERNEL PRINCIPAL COMPONENT ANALYSIS; KERNEL SIGNAL FRACTION ANALYSIS; NOISE REDUCTION; NOISY DATUM; PRINCIPAL COMPONENTS;

EID: 62649127078     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (13)
  • 4
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Scholkopf, A.J. Smola, and K.-R.Muller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1319, 1998.
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Scholkopf, B.1    Smola, A.J.2    Muller, K.R.3
  • 8
    • 62649111503 scopus 로고    scopus 로고
    • dissertation, Colorado State University, Colorado State University, Fort Collins, CO, Spring
    • S. Martin. Techniques in Support Vector Classification. dissertation, Colorado State University, Colorado State University, Fort Collins, CO, Spring 2001.
    • (2001) Techniques in Support Vector Classification
    • Martin, S.1
  • 12
    • 0003928056 scopus 로고
    • Min/max autocorrelation factors for multivariate spatial imagery
    • Technical report, Stanford university, Department of statistics, Stanford university, Department of statistics
    • P. Switzer and A. Green. Min/max autocorrelation factors for multivariate spatial imagery. Technical report, Stanford university, Department of statistics, Stanford university, Department of statistics, 1984.
    • (1984)
    • Switzer, P.1    Green, A.2
  • 13
    • 0023854011 scopus 로고
    • A transformation for odering multispec-tral data in terms of image quality with implications for noise removal
    • January
    • A.A. Green, M. Berman, P. Switzer, and M.D. Craig. A transformation for odering multispec-tral data in terms of image quality with implications for noise removal. IEEE Transactions on Geoscience and Remote Sensing, 26(1):65-74, January 1988.
    • (1988) IEEE Transactions on Geoscience and Remote Sensing , vol.26 , Issue.1 , pp. 65-74
    • Green, A.A.1    Berman, M.2    Switzer, P.3    Craig, M.D.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.