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Volumn 36, Issue 4, 2003, Pages 869-878

Influences of variable scales and activation functions on the performances of multilayer feedforward neural networks

Author keywords

Activation functions; Neural networks; Support vector machine; Variable scales

Indexed keywords

NEURAL NETWORKS;

EID: 0036555952     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(02)00120-6     Document Type: Article
Times cited : (34)

References (33)
  • 1
    • 0023331258 scopus 로고
    • An introduction to computing with neural nets
    • R.P. Lippmann, An introduction to computing with neural nets, IEEE ASSP Mag. 4 (1987) 4-22.
    • (1987) IEEE ASSP Mag. , vol.4 , pp. 4-22
    • Lippmann, R.P.1
  • 4
    • 0345628005 scopus 로고    scopus 로고
    • Three methods to speed up the training of feedforward and feedback perceptrons
    • F. Stager, M. Agarwal, Three methods to speed up the training of feedforward and feedback perceptrons, Neural Networks 10 (8) (1997) 1435-1443.
    • (1997) Neural Networks , vol.10 , Issue.8 , pp. 1435-1443
    • Stager, F.1    Agarwal, M.2
  • 5
    • 0003000735 scopus 로고
    • Faster-learning variations on back-propagation: An empirical study
    • Carnegie Mellon University
    • S.E. Fahlman, Faster-learning variations on back-propagation: an empirical study, Proceedings of the 1988 Connectionist Model Summer School, Carnegie Mellon University, 1989, pp. 38-51.
    • (1989) Proceedings of the 1988 Connectionist Model Summer School , pp. 38-51
    • Fahlman, S.E.1
  • 6
    • 0025536870 scopus 로고
    • Improving the learning speed of 2-layer neural networks by choosing initial values of adaptive weights
    • D. Nguyen, B. Widrow, Improving the learning speed of 2-layer neural networks by choosing initial values of adaptive weights, Proc. IJCNN 3 (1990) 21-26.
    • (1990) Proc. IJCNN , vol.3 , pp. 21-26
    • Nguyen, D.1    Widrow, B.2
  • 7
    • 0028430459 scopus 로고
    • Analysis of the back-propagation algorithm with momentum
    • V.V. Phansalkar, P.S. Sastry, Analysis of the back-propagation algorithm with momentum, IEEE Trans. Neural Networks 5 (3) (1994) 505-507.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.3 , pp. 505-507
    • Phansalkar, V.V.1    Sastry, P.S.2
  • 8
    • 0028425156 scopus 로고    scopus 로고
    • An iterative method for training multilayer networks with threshold functions
    • E.M. Corwin, A.M. Logar, W.J.E. Oldham, An iterative method for training multilayer networks with threshold functions, IEEE Trans. Neural Networks 5 (3) (1999) 507-508.
    • (1999) IEEE Trans. Neural Networks , vol.5 , Issue.3 , pp. 507-508
    • Corwin, E.M.1    Logar, A.M.2    Oldham, W.J.E.3
  • 9
    • 0031028741 scopus 로고    scopus 로고
    • Effective backpropagation training with variable stepsize
    • G.D. Magoulas, M.N. Varhatis, G.S. Androulakis, Effective backpropagation training with variable stepsize, Neural Networks 10 (1) (1997) 69-82.
    • (1997) Neural Networks , vol.10 , Issue.1 , pp. 69-82
    • Magoulas, G.D.1    Varhatis, M.N.2    Androulakis, G.S.3
  • 10
    • 0028426766 scopus 로고
    • An accelerated learning algorithm for multilayer perceptron networks
    • A.G. Parlos, F. Fernandez, A.F. Atiya, et al., An accelerated learning algorithm for multilayer perceptron networks, IEEE Trans. Neural Networks 5 (3) (1994) 493-497.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.3 , pp. 493-497
    • Parlos, A.G.1    Fernandez, F.2    Atiya, A.F.3
  • 11
    • 0032072175 scopus 로고    scopus 로고
    • A successive overrelaxative backpropagation algorithm for neural-network training
    • R.D. Leone, R. Capparuccia, E. Merelli, A successive overrelaxative backpropagation algorithm for neural-network training, IEEE Trans. Neural Networks 9 (3) (1998) 381-387.
    • (1998) IEEE Trans. Neural Networks , vol.9 , Issue.3 , pp. 381-387
    • Leone, R.D.1    Capparuccia, R.2    Merelli, E.3
  • 12
    • 0029182199 scopus 로고
    • An accelerated learning algorithm for multilayer perceptrons: Optimization layer by layer
    • S. Ergezinger, E. Thomsen, An accelerated learning algorithm for multilayer perceptrons: optimization layer by layer, IEEE Trans. Neural Networks 6 (1) (1995) 31-42.
    • (1995) IEEE Trans. Neural Networks , vol.6 , Issue.1 , pp. 31-42
    • Ergezinger, S.1    Thomsen, E.2
  • 13
    • 0033749078 scopus 로고    scopus 로고
    • The layer-wise method and the backpropagation hybrid approach to learning a feedforward neural network
    • N.S. Rubanov, The layer-wise method and the backpropagation hybrid approach to learning a feedforward neural network, IEEE Trans. Neural Networks 11 (2) (2000) 295-305.
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.2 , pp. 295-305
    • Rubanov, N.S.1
  • 14
    • 0032164306 scopus 로고    scopus 로고
    • An optimization method for the topological structures of feed-forward multi-layer neural networks
    • Gao Daqi, Wu Shou yi, An optimization method for the topological structures of feed-forward multi-layer neural networks, Pattern Recognition 31 (9) (1998) 1337-1342.
    • (1998) Pattern Recognition , vol.31 , Issue.9 , pp. 1337-1342
    • Daqi, G.1    WuShou yi2
  • 15
    • 0028425064 scopus 로고
    • SVD-NET: An algorithm that automatically selects network structure
    • D.C. Psichogios, L.H. Ungar, SVD-NET: an algorithm that automatically selects network structure, IEEE Trans. Neural Networks 5 (3) (1994) 513-515.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.3 , pp. 513-515
    • Psichogios, D.C.1    Ungar, L.H.2
  • 16
    • 0030198925 scopus 로고    scopus 로고
    • Characterization of a class of sigmoid functions with applications to neural networks
    • A. Menon, K. Mehrotra, C.K. Mohan, et al., Characterization of a class of sigmoid functions with applications to neural networks, Neural Networks 9 (5) (1996) 819-835.
    • (1996) Neural Networks , vol.9 , Issue.5 , pp. 819-835
    • Menon, A.1    Mehrotra, K.2    Mohan, C.K.3
  • 17
    • 0030584163 scopus 로고    scopus 로고
    • The interchangeability of learning rate and gain in backpropagation neural networks
    • G. Thimm, P. Moerland, E. Fiesler, The interchangeability of learning rate and gain in backpropagation neural networks, Neural Comput. 8 (2) (1996) 451-460.
    • (1996) Neural Comput. , vol.8 , Issue.2 , pp. 451-460
    • Thimm, G.1    Moerland, P.2    Fiesler, E.3
  • 18
    • 0030176172 scopus 로고    scopus 로고
    • A feedforward neural network with function shape autotuning
    • C.-T. Chen, W.-D. Chang, A feedforward neural network with function shape autotuning, Neural Networks 9 (4) (1996) 627-641.
    • (1996) Neural Networks , vol.9 , Issue.4 , pp. 627-641
    • Chen, C.-T.1    Chang, W.-D.2
  • 19
    • 0000595242 scopus 로고
    • Note on learning rate schedules for stochastic optimization
    • R.P. Lippmann et al. (Eds.)
    • D. Christian, M. John, Note on learning rate schedules for stochastic optimization, in: R.P. Lippmann et al. (Eds.), Neural Information Processing Systems, 1991, pp. 832-838.
    • (1991) Neural Information Processing Systems , pp. 832-838
    • Christian, D.1    John, M.2
  • 20
    • 0032643084 scopus 로고    scopus 로고
    • Multilayer feedforward networks with adaptive spline activation function
    • S. Guarnieri, F. Piazza, A. Uncini, Multilayer feedforward networks with adaptive spline activation function, IEEE Trans. Neural Networks 10 (3) (1999) 672-684.
    • (1999) IEEE Trans. Neural Networks , vol.10 , Issue.3 , pp. 672-684
    • Guarnieri, S.1    Piazza, F.2    Uncini, A.3
  • 21
    • 0028424954 scopus 로고
    • Computing second derivatives in feed-forward neural networks: A review
    • W.L. Buntine, A.S. Weigend, Computing second derivatives in feed-forward neural networks: a review, IEEE Trans. Neural Networks 5 (3) (1994) 480-488.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.3 , pp. 480-488
    • Buntine, W.L.1    Weigend, A.S.2
  • 22
    • 0034187311 scopus 로고    scopus 로고
    • Classification ability of single hidden layer feedforward neural networks
    • G.-B. Huang, Y.-Q. Chen, H.A. Babri, Classification ability of single hidden layer feedforward neural networks, IEEE Trans. Neural Networks 11 (3) (2000) 799-801.
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.3 , pp. 799-801
    • Huang, G.-B.1    Chen, Y.-Q.2    Babri, H.A.3
  • 23
    • 0031673055 scopus 로고    scopus 로고
    • Upper bounds on the number of hidden neurons in feedforward networks with arbitrary bounded nonlinear activation function
    • G.-B. Huang, H.A. Babri, Upper bounds on the number of hidden neurons in feedforward networks with arbitrary bounded nonlinear activation function, IEEE Trans. Neural Networks 9 (1) (1998) 224-228.
    • (1998) IEEE Trans. Neural Networks , vol.9 , Issue.1 , pp. 224-228
    • Huang, G.-B.1    Babri, H.A.2
  • 24
    • 0029410181 scopus 로고
    • The effects of quantization on multilayer neural networks
    • G. Dundar, K. Rose, The effects of quantization on multilayer neural networks, IEEE Trans. Neural Networks 6 (6) (1995) 1445-1451.
    • (1995) IEEE Trans. Neural Networks , vol.6 , Issue.6 , pp. 1445-1451
    • Dundar, G.1    Rose, K.2
  • 25
    • 0033100852 scopus 로고    scopus 로고
    • Worst case analysis of weight inaccuracy effects in multi perceptrons
    • D. Anguita, S. Ridella, S. Rovetta, Worst case analysis of weight inaccuracy effects in multi perceptrons, IEEE Trans. Neural Networks 10 (2) (1999) 415-419.
    • (1999) IEEE Trans. Neural Networks , vol.10 , Issue.2 , pp. 415-419
    • Anguita, D.1    Ridella, S.2    Rovetta, S.3
  • 26
    • 0032594959 scopus 로고    scopus 로고
    • An overview of statistical learning theory
    • V.N. Vapnik, An overview of statistical learning theory, IEEE Trans. Neural Networks 10 (5) (1999) 988-999.
    • (1999) IEEE Trans. Neural Networks , vol.10 , Issue.5 , pp. 988-999
    • Vapnik, V.N.1
  • 27
    • 0034187293 scopus 로고    scopus 로고
    • Modified cascade-correlation learning for classification
    • M. Lehtokangas, Modified cascade-correlation learning for classification, IEEE Trans. Neural Networks 11 (3) (2000) 795-798.
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.3 , pp. 795-798
    • Lehtokangas, M.1
  • 28
    • 0032634974 scopus 로고    scopus 로고
    • Training multilayer perceptron classifiers based on a modified support vector method
    • J.A.K. Suykens, J. Vandewalle, Training multilayer perceptron classifiers based on a modified support vector method, IEEE Trans. Neural Networks 10 (4) (1999) 907-911.
    • (1999) IEEE Trans. Neural Networks , vol.10 , Issue.4 , pp. 907-911
    • Suykens, J.A.K.1    Vandewalle, J.2
  • 29
    • 0032690356 scopus 로고    scopus 로고
    • Reformulated radial basis neural networks trained by gradient descent
    • N.B. Karayiannis, Reformulated radial basis neural networks trained by gradient descent, IEEE Trans. Neural Networks 10 (3) (1999) 1121-1138.
    • (1999) IEEE Trans. Neural Networks , vol.10 , Issue.3 , pp. 1121-1138
    • Karayiannis, N.B.1
  • 30
    • 0348209367 scopus 로고    scopus 로고
    • ftp://ftp.ics.uci.edu/pub/mechine-learning-databases
  • 31
    • 0346318771 scopus 로고    scopus 로고
    • http://www.ics.uci.edu/~mlearn.
  • 32
    • 0023843391 scopus 로고    scopus 로고
    • Analysis of hidden units in a layered network trained to classify sonar targets
    • R.P. Gormann, T.J. Sejnowski, Analysis of hidden units in a layered network trained to classify sonar targets, Neural Networks 1 (1) (1998) 75-89.
    • (1998) Neural Networks , vol.1 , Issue.1 , pp. 75-89
    • Gormann, R.P.1    Sejnowski, T.J.2
  • 33
    • 0029000115 scopus 로고
    • An algorithm to generate radial basis function (RBF)-like nets for classiffication problems
    • A. Roy, S. Govil, P. Miranda, An algorithm to generate radial basis function (RBF)-like nets for classification problems, Neural Networks 8 (2) (1995) 179-201.
    • (1995) Neural Networks , vol.8 , Issue.2 , pp. 179-201
    • Roy, A.1    Govil, S.2    Miranda, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.