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Volumn 7, Issue 6, 1996, Pages 1503-1506

Error-minimizing dead zone for basis function networks

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EID: 17044414558     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.548178     Document Type: Article
Times cited : (18)

References (14)
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    • Powell, M.J.D.1
  • 2
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    • Networks and the best approximation property
    • F. Girosi and T. Poggio, "Networks and the best approximation property," Biol. Cybern., vol. 63, pp. 169-176, 1990.
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    • Girosi, F.1    Poggio, T.2
  • 3
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    • Universal approximation using radial basis function networks
    • J. Park and I. W. Sandberg. "Universal approximation using radial basis function networks," Neural Computa., vol. 3, pp. 246-257, 1991.
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    • Park, J.1    Sandberg, I.W.2
  • 4
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    • Gaussian networks for direct adaptive control
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    • R. M. Sanner and J.-J. E. Slotine, "Gaussian networks for direct adaptive control," IEEE Trans. Neural Networks, vol. 3, pp. 837-863, Nov. 1992.
    • (1992) IEEE Trans. Neural Networks , vol.3 , pp. 837-863
    • Sanner, R.M.1    Slotine, J.-J.E.2
  • 5
    • 0029202959 scopus 로고
    • Multiplication-free radial basis function network
    • Seattle, WA
    • S. Kampl and M. Heiss, "Multiplication-free radial basis function network," in Proc. Amer. Contr. Conf. (ACC 95), Seattle, WA, 1995, pp. 3782-3785.
    • (1995) Proc. Amer. Contr. Conf. (ACC 95) , pp. 3782-3785
    • Kampl, S.1    Heiss, M.2
  • 7
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    • Learning of linearly interpolated input-ouput maps
    • in German
    • M. Heiss, D. Heiss, and S. Kampl, "Learning of linearly interpolated input-ouput maps (in German)," Automatisierungstechnik, vol. 42. no. 11, pp. 497-506, 1994.
    • (1994) Automatisierungstechnik , vol.42 , Issue.11 , pp. 497-506
    • Heiss, M.1    Heiss, D.2    Kampl, S.3
  • 8
    • 0000857773 scopus 로고
    • Identification of nonlinear processes using reciprocal multiquadric functions
    • M. Pottmann and D. E. Seborg, "Identification of nonlinear processes using reciprocal multiquadric functions," J. Process Contr., vol. 2, no. 4, pp. 189-203, 1992.
    • (1992) J. Process Contr. , vol.2 , Issue.4 , pp. 189-203
    • Pottmann, M.1    Seborg, D.E.2
  • 10
    • 33747622815 scopus 로고
    • Neural networks for adaptive control and recursive identification: A theoretical framework
    • H. L. Trentelman and J. C. Willems, Eds., Boston, MA: Birkhauser, ch. 11
    • J.-J. E. Slotine and R. M. Sanner, "Neural networks for adaptive control and recursive identification: A theoretical framework," in Essays on Control: Perspectives in The Theory and its Application, H. L. Trentelman and J. C. Willems, Eds., Boston, MA: Birkhauser, 1993, ch. 11, pp. 381-436.
    • (1993) Essays on Control: Perspectives in the Theory and Its Application , pp. 381-436
    • Slotine, J.-J.E.1    Sanner, R.M.2
  • 13
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    • A dead-zone approach in nonlinear adaptive control using neural networks
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    • F.-C. Chen, "A dead-zone approach in nonlinear adaptive control using neural networks," in Proc. Conf. Decision and Contr. (CDC 91), Brighton, U.K., 1991, pp. 156-161.
    • (1991) Proc. Conf. Decision and Contr. (CDC 91) , pp. 156-161
    • Chen, F.-C.1
  • 14
    • 0028531258 scopus 로고
    • Reinforcement learning or tracking of input-output-maps
    • M. Heiss, "Reinforcement learning or tracking of input-output-maps," Appl. Artificial Intell., vol. 8, no. 4, pp. 483-496, 1994.
    • (1994) Appl. Artificial Intell. , vol.8 , Issue.4 , pp. 483-496
    • Heiss, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.