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Volumn 57, Issue 1-4, 2004, Pages 485-492

Maximum neural network with nonlinear self-feedback for maximum clique problem

Author keywords

Maximum clique problem; Maximum neural network; Nonlinear self feedback

Indexed keywords

COMPUTER SIMULATION; NONLINEAR SYSTEMS; PARALLEL ALGORITHMS;

EID: 1542471408     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2004.01.001     Document Type: Article
Times cited : (9)

References (11)
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  • 2
    • 0030125301 scopus 로고    scopus 로고
    • Comparisons of energy-descent optimization algorithms for maximum clique problems
    • E79-A
    • Funabiki N. Nishikawa S. Comparisons of energy-descent optimization algorithms for maximum clique problems IEICE Trans. Fundamentals E79-A 4 1996 452-460
    • (1996) IEICE Trans. Fundamentals , Issue.4 , pp. 452-460
    • Funabiki, N.1    Nishikawa, S.2
  • 3
    • 0037118567 scopus 로고    scopus 로고
    • A novel chaotic search for quadratic assignment problems
    • Hasegawa M. Ikeguchi T. Aihara K. Itoh K. A novel chaotic search for quadratic assignment problems Eur. J. Oper. Res. 139 3 2002 543-556
    • (2002) Eur. J. Oper. Res. , vol.139 , Issue.3 , pp. 543-556
    • Hasegawa, M.1    Ikeguchi, T.2    Aihara, K.3    Itoh, K.4
  • 5
    • 0003037529 scopus 로고
    • Reducibility among combinatorial problems
    • R. Miller, & J. Thatcher (Eds.), New York: Plenum Press
    • Karp R.M. Reducibility among combinatorial problems, in: Miller R. Thatcher J. (Eds.), Complexity of Computer Computations 1972 85-104 Plenum Press New York
    • (1972) Complexity of Computer Computations , pp. 85-104
    • Karp, R.M.1
  • 7
    • 0026897860 scopus 로고
    • A branch and bound algorithm for the maximum clique problem
    • Pardalos P.M. Rodger G.P. A branch and bound algorithm for the maximum clique problem Comput. Oper. Res. 19 5 1992 363-375
    • (1992) Comput. Oper. Res. , vol.19 , Issue.5 , pp. 363-375
    • Pardalos, P.M.1    Rodger, G.P.2
  • 8
    • 0344194652 scopus 로고
    • An artificial maximum neural network: A winner-take-all neuron model forcing the state of the system in a solution domain
    • Takefuji Y. Lee K. Aiso H. An artificial maximum neural network: a winner-take-all neuron model forcing the state of the system in a solution domain Biol. Cybernet. 67 3 1992 243-251
    • (1992) Biol. Cybernet. , vol.67 , Issue.3 , pp. 243-251
    • Takefuji, Y.1    Lee, K.2    Aiso, H.3
  • 10
    • 0034270883 scopus 로고    scopus 로고
    • A proposal neural filter: A constraint resolution scheme of neural networks for combinatorial optimization problems
    • E83-A
    • Takenaka Y. Funabiki N. Higashino T. A proposal neural filter: a constraint resolution scheme of neural networks for combinatorial optimization problems IEICE Trans. Fundamentals E83-A 9 2000 1815-1823
    • (2000) IEICE Trans. Fundamentals , Issue.9 , pp. 1815-1823
    • Takenaka, Y.1    Funabiki, N.2    Higashino, T.3
  • 11
    • 0042708783 scopus 로고
    • A randomized algorithm for finding a near-maximum clique and its experimental evaluations
    • J76-D-I
    • Yamada Y. Tomita E. Takahashi H. A randomized algorithm for finding a near-maximum clique and its experimental evaluations IEICE Trans. Inf. J76-D-I 2 1993 46-53
    • (1993) IEICE Trans. Inf. , Issue.2 , pp. 46-53
    • Yamada, Y.1    Tomita, E.2    Takahashi, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.