메뉴 건너뛰기




Volumn , Issue , 2001, Pages 153-162

Simple unit-pruning with gain-changing training

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; BRAIN; GAIN CONTROL; MEDICAL IMAGING; PROBLEM SOLVING; SPURIOUS SIGNAL NOISE;

EID: 0035784067     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (23)
  • 3
    • 0031142667 scopus 로고    scopus 로고
    • An iterative pruning algorithm for feedforward neural networks
    • May
    • G. Castellano, A.M. Fanelli and M. Pelillo, "An iterative pruning algorithm for feedforward neural networks," IEEE Trans. Neural Networks, vol. 8, no. 3, pp. 519-531, May 1997.
    • (1997) IEEE Trans. Neural Networks , vol.8 , Issue.3 , pp. 519-531
    • Castellano, G.1    Fanelli, A.M.2    Pelillo, M.3
  • 4
    • 0000473247 scopus 로고
    • A back-propagation algorithm with optimal use of hidden units
    • D.S. Touretzky (ed.)
    • Y. Chanvin, "A back-propagation algorithm with optimal use of hidden units," in D.S. Touretzky (ed.), Advances in Neural Information Processing, 1989, vol. 1, pp. 519-526.
    • (1989) Advances in Neural Information Processing , vol.1 , pp. 519-526
    • Chanvin, Y.1
  • 6
    • 0026221027 scopus 로고
    • An information criterion for optimal neural network selection
    • D.B. Fogel, "An information criterion for optimal neural network selection," IEEE Trans. Neural Networks, vol. 2, no. 5, pp. 490-497, 1991.
    • (1991) IEEE Trans. Neural Networks , vol.2 , Issue.5 , pp. 490-497
    • Fogel, D.B.1
  • 7
    • 0025547727 scopus 로고
    • Novel back propagation algorithm for reduction of hidden units and acceleration of convergence using artificial selection
    • Jun.
    • M. Hagiwara, "Novel back propagation algorithm for reduction of hidden units and acceleration of convergence using artificial selection," in Proc. Int. Joint Conf. Neural Networks, Jun. 1990, vol. II, pp. 625-630.
    • (1990) Proc. Int. Joint Conf. Neural Networks , vol.2 , pp. 625-630
    • Hagiwara, M.1
  • 8
    • 0030130724 scopus 로고    scopus 로고
    • Structural learning with forgetting
    • M. Ishikawa, "Structural learning with forgetting," Neural Networks, vol. 9, no. 3, pp. 509 521, 1996.
    • (1996) Neural Networks , vol.9 , Issue.3 , pp. 509-521
    • Ishikawa, M.1
  • 9
    • 0000974760 scopus 로고
    • Generalizing smoothness constraints from discrete samples
    • C. Ji, R.R. Snapp and D. Psaltis, "Generalizing smoothness constraints from discrete samples," Neural Computation, vol. 2, no. 1, pp. 188-197, 1990.
    • (1990) Neural Computation , vol.2 , Issue.1 , pp. 188-197
    • Ji, C.1    Snapp, R.R.2    Psaltis, D.3
  • 10
    • 0000164013 scopus 로고
    • A method to determine the number of hidden units of three layered neural networks by information criteria
    • T. Kurita, "A method to determine the number of hidden units of three layered neural networks by information criteria," Trails. IEICE D-II, vol. J73-D-II, no. 11, pp. 1872-1878, 1990.
    • (1990) Trails. IEICE D-II , vol.J73-D-II , Issue.11 , pp. 1872-1878
    • Kurita, T.1
  • 11
    • 0028544395 scopus 로고
    • Network information criterion - Determining the number of hidden units for an artificial neural network model
    • N. Murata, S. Yoshizawa and S. Amari, "Network information criterion - Determining the number of hidden units for an artificial neural network model," IEEE Trans. Neural Networks, vol. 5, no. 6, pp. 865-872, 1994.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.6 , pp. 865-872
    • Murata, N.1    Yoshizawa, S.2    Amari, S.3
  • 12
    • 0001765492 scopus 로고
    • Simplifying neural networks by soft weight-sharing
    • S.J. Nowlan and G.E. Hinton, "Simplifying neural networks by soft weight-sharing," Neural Computation, vol. 4, no. 4, pp. 473-493, 1992.
    • (1992) Neural Computation , vol.4 , Issue.4 , pp. 473-493
    • Nowlan, S.J.1    Hinton, G.E.2
  • 13
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • MA: MIT Press, chap. 8
    • D.E. Rumelhart, G.E. Hinton and R.J. Williams, Learning internal representations by error propagation, MA: MIT Press, vol. 1 of Parallel Distributed Processing, chap. 8, pp. 318-362, 1986.
    • (1986) Parallel Distributed Processing , vol.1 , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 14
    • 0026017007 scopus 로고
    • Creating artificial neural networks that generalize
    • J. Sietsma and R.J.F. Dow, "Creating artificial neural networks that generalize," Neural Networks, vol. 4, no. 1, pp. 67-69, 1991.
    • (1991) Neural Networks , vol.4 , Issue.1 , pp. 67-69
    • Sietsma, J.1    Dow, R.J.F.2
  • 16
    • 0033334510 scopus 로고    scopus 로고
    • Efficient approximation of a neural filter for quantum noise removal in X-ray images
    • Y.-H. Hu et al. (eds.), Madison, WI, Aug.
    • K. Suzuki, I. Horiba and N. Sugie, "Efficient approximation of a neural filter for quantum noise removal in X-ray images," in Y.-H. Hu et al. (eds.), Proc. IEEE Int. Workshop Neural Networks for Signal Processing IX, Madison, WI, Aug. 1999, pp. 370-379.
    • (1999) Proc. IEEE Int. Workshop Neural Networks for Signal Processing IX , pp. 370-379
    • Suzuki, K.1    Horiba, I.2    Sugie, N.3
  • 17
    • 0035251045 scopus 로고    scopus 로고
    • A simple neural network pruning algorithm with application to filter synthesis
    • Feb.
    • K. Suzuki, I. Horiba and N. Sugie, "A Simple Neural Network Pruning Algorithm with Application to Filter Synthesis," Neural Processing Letters, vol. 13, no. 1, pp. 43-53, Feb. 2001.
    • (2001) Neural Processing Letters , vol.13 , Issue.1 , pp. 43-53
    • Suzuki, K.1    Horiba, I.2    Sugie, N.3
  • 18
  • 19
    • 0001426628 scopus 로고    scopus 로고
    • A recurrent neural filter for reducing noise in medical X-ray image sequences
    • Kitakyushu, Japan, Oct.
    • K. Suzuki, I. Horiba, N. Sugie and M. Nanki, "A Recurrent Neural Filter for Reducing Noise in Medical X-ray Image Sequences," in Proc. Int. Conf. Neural Information Processing, Kitakyushu, Japan, Oct. 1998, vol. 1, pp. 157-160.
    • (1998) Proc. Int. Conf. Neural Information Processing , vol.1 , pp. 157-160
    • Suzuki, K.1    Horiba, I.2    Sugie, N.3    Nanki, M.4
  • 21
    • 0026367426 scopus 로고
    • Generalization by weight-elimination applied to currency exchange rate prediction
    • Seattle, WA
    • A.S. Weigend, D.E. Rumelhart and B.A. Huberman, "Generalization by weight-elimination applied to currency exchange rate prediction," in Proc. Int. Joint Conf. Neural Networks, Seattle, WA, 1991, vol. 1, pp. 837-841.
    • (1991) Proc. Int. Joint Conf. Neural Networks , vol.1 , pp. 837-841
    • Weigend, A.S.1    Rumelhart, D.E.2    Huberman, B.A.3
  • 22
    • 0027561348 scopus 로고
    • A new class of nonlinear filters - Neural filters
    • March
    • L. Yin, J. Astola and Y. Neuvo, "A new class of nonlinear filters - Neural filters," IEEE Trans. Signal Processing, vol. 41, no. 3, pp. 1201-1222, March 1993.
    • (1993) IEEE Trans. Signal Processing , vol.41 , Issue.3 , pp. 1201-1222
    • Yin, L.1    Astola, J.2    Neuvo, Y.3
  • 23
    • 0028375309 scopus 로고
    • Adaptive multistage weighted order statistic filters based on the back propagation algorithm
    • Feb.
    • L. Yin, J. Astola and Y. Neuvo, "Adaptive multistage weighted order statistic filters based on the back propagation algorithm," IEEE Trans. Signal Processing, vol. 42, pp. 419-422, Feb. 1994.
    • (1994) IEEE Trans. Signal Processing , vol.42 , pp. 419-422
    • Yin, L.1    Astola, J.2    Neuvo, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.