메뉴 건너뛰기




Volumn 16, Issue 4, 2006, Pages 295-303

A delayed neural network method for solving convex optimization problems

Author keywords

Convex programming; Delayed projection neural network; Global exponential stability

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COMPUTER PROGRAM; NONLINEAR SYSTEM;

EID: 33748653602     PISSN: 01290657     EISSN: None     Source Type: Journal    
DOI: 10.1142/S012906570600069X     Document Type: Article
Times cited : (16)

References (24)
  • 3
    • 0020118274 scopus 로고
    • Neural networks and physical systems with emergent collective computational ability
    • J. J. Hopfield, Neural networks and physical systems with emergent collective computational ability, in Proc. National Academy of Sciences (USA), Biophysics 79 (1982) 2554-2558.
    • (1982) Proc. National Academy of Sciences (USA), Biophysics , vol.79 , pp. 2554-2558
    • Hopfield, J.J.1
  • 4
    • 0022721216 scopus 로고
    • Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit
    • D. W. Tank and J. J. Hopfield, Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit, IEEE Trans. on Circuits and Systems 33 (1986) 533-541.
    • (1986) IEEE Trans. on Circuits and Systems , vol.33 , pp. 533-541
    • Tank, D.W.1    Hopfield, J.J.2
  • 7
    • 0033233946 scopus 로고    scopus 로고
    • A neural network methodology and strategy of quadratic optimisation
    • A. Wu and P. K. S. Tam, A neural network methodology and strategy of quadratic optimisation, Neural Computing and Application 8 (1999) 283-289.
    • (1999) Neural Computing and Application , vol.8 , pp. 283-289
    • Wu, A.1    Tam, P.K.S.2
  • 8
    • 17944387843 scopus 로고    scopus 로고
    • A dual neural network for convex quadratic programming subject to linear equality and inequality constraints
    • Y. Zhang and J. Wang, A dual neural network for convex quadratic programming subject to linear equality and inequality constraints, Physics Letters A 298 (2002) 271-278.
    • (2002) Physics Letters A , vol.298 , pp. 271-278
    • Zhang, Y.1    Wang, J.2
  • 9
    • 0035903532 scopus 로고    scopus 로고
    • A high performance neural network for solving nonlinear programming problems with hybrid constraints
    • Q. Tao, J. Cao, M. Xue and H. Qiao, A high performance neural network for solving nonlinear programming problems with hybrid constraints, Physics Letters A 288 (2001) 88-94.
    • (2001) Physics Letters A , vol.288 , pp. 88-94
    • Tao, Q.1    Cao, J.2    Xue, M.3    Qiao, H.4
  • 10
    • 0347817670 scopus 로고    scopus 로고
    • A simple and high performance neural network for quadratic programming problems
    • Q. Tao, J. Cao and D. Sun, A simple and high performance neural network for quadratic programming problems, Applied Mathematics and Computation 124 (2001) 251-260.
    • (2001) Applied Mathematics and Computation , vol.124 , pp. 251-260
    • Tao, Q.1    Cao, J.2    Sun, D.3
  • 11
    • 4143078142 scopus 로고    scopus 로고
    • A recurrent neural networks with exponential convergence for solving convex quadratic program and related linear piecewise equations
    • Y. Xia, G. Feng and J. Wang, A recurrent neural networks with exponential convergence for solving convex quadratic program and related linear piecewise equations, Neural Networks 17 (2004) 1003-1015.
    • (2004) Neural Networks , vol.17 , pp. 1003-1015
    • Xia, Y.1    Feng, G.2    Wang, J.3
  • 12
    • 0036539447 scopus 로고    scopus 로고
    • A projection neural network and its application to constrained optimization problems
    • Y. Xia, H. Leung and J. Wang, A projection neural network and its application to constrained optimization problems, IEEE Trans. Circuits and Systems-I 49 (2002) 447-458.
    • (2002) IEEE Trans. Circuits and Systems-I , vol.49 , pp. 447-458
    • Xia, Y.1    Leung, H.2    Wang, J.3
  • 13
    • 3843138428 scopus 로고    scopus 로고
    • A recurrent neural networks for nonlinear convex optimization subject to nonlinear inequality constraints
    • Y. Xia and J. Wang, A recurrent neural networks for nonlinear convex optimization subject to nonlinear inequality constraints, IEEE Trans. Circuits and Systems-I 51 (2004) 1385-1394.
    • (2004) IEEE Trans. Circuits and Systems-I , vol.51 , pp. 1385-1394
    • Xia, Y.1    Wang, J.2
  • 14
    • 2542589347 scopus 로고    scopus 로고
    • A novel neural network for nonlinear convex programming
    • X. B. Gao, A novel neural network for nonlinear convex programming, IEEE Trans. Neural Networks 15 (2004) 613-621.
    • (2004) IEEE Trans. Neural Networks , vol.15 , pp. 613-621
    • Gao, X.B.1
  • 15
    • 0742268988 scopus 로고    scopus 로고
    • A high-performance feedback neural network for solving convex nonlinear programming problems
    • Y. Leung and X. B. Gao, A high-performance feedback neural network for solving convex nonlinear programming problems, IEEE Trans. Neural Networks 14 (2003) 1469-1477.
    • (2003) IEEE Trans. Neural Networks , vol.14 , pp. 1469-1477
    • Leung, Y.1    Gao, X.B.2
  • 16
    • 0033640635 scopus 로고    scopus 로고
    • Neurocomputing with time delay analysis for solving convex quadratic programming problems
    • Y. H. Chen and S. C. Fang, Neurocomputing with time delay analysis for solving convex quadratic programming problems, IEEE Trans. Neural Networks 11 (2000) 230-240.
    • (2000) IEEE Trans. Neural Networks , vol.11 , pp. 230-240
    • Chen, Y.H.1    Fang, S.C.2
  • 17
    • 23044474397 scopus 로고    scopus 로고
    • A delayed neural network for solving linear projection equations and its analysis
    • Q. Liu, J. Cao and Y. Xia, A delayed neural network for solving linear projection equations and its analysis, IEEE Trans. Neural Networks 16 (2005) 834-843.
    • (2005) IEEE Trans. Neural Networks , vol.16 , pp. 834-843
    • Liu, Q.1    Cao, J.2    Xia, Y.3
  • 18
    • 0001284544 scopus 로고    scopus 로고
    • A recurrent neural networks for nonlinear optimization with a continuously differentiable object function and bound constraints
    • X. B. Liang and J. Wang, A recurrent neural networks for nonlinear optimization with a continuously differentiable object function and bound constraints, IEEE Trans. Neural Networks 11 (2000) 1251-1262.
    • (2000) IEEE Trans. Neural Networks , vol.11 , pp. 1251-1262
    • Liang, X.B.1    Wang, J.2
  • 19
    • 15344350315 scopus 로고    scopus 로고
    • A recurrent neural networks for nonlinear convex optimization subject to linear constraints
    • Y. Xia and J. Wang, A recurrent neural networks for nonlinear convex optimization subject to linear constraints, IEEE Trans. Neural Networks 16 (2005) 379-386.
    • (2005) IEEE Trans. Neural Networks , vol.16 , pp. 379-386
    • Xia, Y.1    Wang, J.2
  • 21
    • 0029345226 scopus 로고
    • New conditions for global stability of neural networks with application to linear and quadratuic programming problems
    • M. Forti and A. Tesi, New conditions for global stability of neural networks with application to linear and quadratuic programming problems, IEEE Trans. Circuits and System-I 42 (1995) 354-366.
    • (1995) IEEE Trans. Circuits and System-I , vol.42 , pp. 354-366
    • Forti, M.1    Tesi, A.2
  • 22
    • 0028320687 scopus 로고
    • A deterministic annealing neural network for convex programming
    • J. Wang, A deterministic annealing neural network for convex programming, Neural Networks 7 (1994) 629-641.
    • (1994) Neural Networks , vol.7 , pp. 629-641
    • Wang, J.1
  • 23
    • 0030085605 scopus 로고    scopus 로고
    • Dynamic system, variational inequalities, and control theoretic models for predicting time-varying urban network flows
    • T. L. Friesz, D. H. Bernstein and R. Stough, Dynamic system, variational inequalities, and control theoretic models for predicting time-varying urban network flows, Transportation Science 30 (1996) 14-31.
    • (1996) Transportation Science , vol.30 , pp. 14-31
    • Friesz, T.L.1    Bernstein, D.H.2    Stough, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.