메뉴 건너뛰기




Volumn 11, Issue 3-4, 2003, Pages 156-160

Evolving fault-tolerant neural networks

Author keywords

Fault tolerance; Fault tolerant neural networks; Generalisation ability; Genetic algorithm

Indexed keywords

COMPUTER SIMULATION; CONFORMAL MAPPING; DECODING; GENETIC ALGORITHMS; GRAPH THEORY; INTEGRATED CIRCUIT LAYOUT; LEARNING ALGORITHMS; MATRIX ALGEBRA; OPTIMIZATION; SONAR; VECTORS; VLSI CIRCUITS;

EID: 0038792238     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-003-0353-4     Document Type: Article
Times cited : (41)

References (16)
  • 2
    • 0027668417 scopus 로고
    • Determining and improving the fault tolerance of multilayer perceptions in a pattern-recognition application
    • Emmerson MD, Damper RI. (1993) Determining and improving the fault tolerance of multilayer perceptions in a pattern-recognition application. IEEE Trans Neural Networks 4(5): 788-793
    • (1993) IEEE Trans Neural Networks , vol.4 , Issue.5 , pp. 788-793
    • Emmerson, M.D.1    Damper, R.I.2
  • 4
    • 0029269583 scopus 로고
    • Complete and partial fault tolerance of feedforward neural nets
    • Phatak DS, Koren I. (1995) Complete and partial fault tolerance of feedforward neural nets: IEEE Trans Neural Networks 6(2): 446-456
    • (1995) IEEE Trans Neural Networks , vol.6 , Issue.2 , pp. 446-456
    • Phatak, D.S.1    Koren, I.2
  • 8
    • 0030649974 scopus 로고    scopus 로고
    • A learning algorithm for fault tolerant feedforward neural networks
    • Hammadi NC, Ito H (1997) A learning algorithm for fault tolerant feedforward neural networks: IEICE Trans Information and Systems 80(1): 21-27
    • (1997) IEICE Trans Information and Systems , vol.80 , Issue.1 , pp. 21-27
    • Hammadi, N.C.1    Ito, H.2
  • 9
    • 0035505587 scopus 로고    scopus 로고
    • Distributed fault tolerance in optimal interpolative nets
    • Simon D. (2001) Distributed fault tolerance in optimal interpolative nets. IEEE Trans Neural Networks 12(6): 1348-1357
    • (2001) IEEE Trans Neural Networks , vol.12 , Issue.6 , pp. 1348-1357
    • Simon, D.1
  • 10
    • 0032163167 scopus 로고
    • Synthesis of fault-tolerant feedforward neural networks using minimax optimisation
    • Deodhare D, Vidyasagar M, Keerthi SS. (1993) Synthesis of fault-tolerant feedforward neural networks using minimax optimisation. IEEE Trans Neural Networks 9(5): 891-900
    • (1993) IEEE Trans Neural Networks , vol.9 , Issue.5 , pp. 891-900
    • Deodhare, D.1    Vidyasagar, M.2    Keerthi, S.S.3
  • 13
    • 0022471098 scopus 로고
    • Learning representations by backpropagating errors
    • Rumelhart DE, Hinton G, Williams R. (1986) Learning representations by backpropagating errors: Nature 323(9): 318-362
    • (1986) Nature , vol.323 , Issue.9 , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.2    Williams, R.3
  • 14
    • 0023843391 scopus 로고
    • Analysis of hidden units in a layered network trained to classify sonar targets
    • Gorman RP, Sejnowski TJ (1988) Analysis of hidden units in a layered network trained to classify sonar targets. Neural Networks 1: 75-89
    • (1988) Neural Networks , vol.1 , pp. 75-89
    • Gorman, R.P.1    Sejnowski, T.J.2
  • 15
    • 0033362601 scopus 로고    scopus 로고
    • Evolving artificial neural networks
    • Yao X. (1999) Evolving artificial neural networks. Proc IEEE 87(9): 1423-1447.
    • (1999) Proc IEEE , vol.87 , Issue.9 , pp. 1423-1447
    • Yao, X.1
  • 16
    • 0036567392 scopus 로고    scopus 로고
    • Ensembling neural networks: Many could be better than all
    • Zhou Z-H, Wu J, Tang W. (2002) Ensembling neural networks: many could be better than all. Artificial Intelligence 137(1-2): 239-263
    • (2002) Artificial Intelligence , vol.137 , Issue.1-2 , pp. 239-263
    • Zhou, Z.-H.1    Wu, J.2    Tang, W.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.