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Volumn 15, Issue 2, 2000, Pages 618-621

On Gaussian radial basis function approximations: interpretation, extensions, and learning strategies

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN DISTRIBUTION; HEAT CONDUCTION; IMAGE SEGMENTATION; LEARNING SYSTEMS; PROBABILITY DENSITY FUNCTION; RADIAL BASIS FUNCTION NETWORKS;

EID: 0141571972     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article
Times cited : (29)

References (16)
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    • Broomhead, D.1    Lowe, D.2
  • 2
    • 0000672424 scopus 로고
    • Fast learning in networks of locally-tuned processing units
    • J. Moody and C. Darken, "Fast learning in networks of locally-tuned processing units," Neural Computation, vol. 1, pp. 281-294, 1989.
    • (1989) Neural Computation , vol.1 , pp. 281-294
    • Moody, J.1    Darken, C.2
  • 3
    • 0025490985 scopus 로고
    • Networks for approximation and learning
    • T. Poggio and F. Girosi, "Networks for approximation and learning," Proc. of the IEEE, vol. 78, pp. 1481-1497, 1990.
    • (1990) Proc. of the IEEE , vol.78 , pp. 1481-1497
    • Poggio, T.1    Girosi, F.2
  • 7
    • 0000307012 scopus 로고    scopus 로고
    • Combined learning and use for a mixture model equivalent to the RBF classifier
    • D. Miller and H. Uyar, "Combined learning and use for a mixture model equivalent to the RBF classifier," Neural Computation, vol. 10, pp. 281-293, 1998.
    • (1998) Neural Computation , vol.10 , pp. 281-293
    • Miller, D.1    Uyar, H.2
  • 8
    • 0030109050 scopus 로고    scopus 로고
    • Nonparametric estimation and classification using radial basis functions
    • A. Krzyzak, T. Linder, and G. Lugosi, "Nonparametric estimation and classification using radial basis functions," IEEE Trans, on Neural Networks, vol. 7, pp. 475-487, 1996.
    • (1996) IEEE Trans, on Neural Networks , vol.7 , pp. 475-487
    • Krzyzak, A.1    Linder, T.2    Lugosi, G.3
  • 9
    • 0027693932 scopus 로고
    • Hybrid learning algorithm for Gaussian potential function networks
    • C. Chen, W. Chen, and F. Chang, "Hybrid learning algorithm for Gaussian potential function networks," IEE Proc.-D, vol. 140, pp. 442-448, 1993.
    • (1993) IEE Proc.-D , vol.140 , pp. 442-448
    • Chen, C.1    Chen, W.2    Chang, F.3
  • 11
    • 0032122726 scopus 로고    scopus 로고
    • Conditional fuzzy clustering in the design of radial basis function neural networks
    • W. Pedrycz, "Conditional fuzzy clustering in the design of radial basis function neural networks," IEEE Trans. on Neural Networks, vol. 9, pp. 601-612, 1998.
    • (1998) IEEE Trans. on Neural Networks , vol.9 , pp. 601-612
    • Pedrycz, W.1
  • 14
    • 84864066505 scopus 로고    scopus 로고
    • A new parameter estimation method for Gaussian mixtures
    • M. Kearns, S. Solla, and D. Cohn, eds., MIT Press
    • Y. Singer and M. Warmuth, "A new parameter estimation method for Gaussian mixtures," in Advances in Neural Inform. Proc. Systems 11 (M. Kearns, S. Solla, and D. Cohn, eds.), MIT Press, 1999.
    • (1999) Advances in Neural Inform. Proc. Systems , vol.11
    • Singer, Y.1    Warmuth, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.