These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

248 related articles for article (PubMed ID: 18390304)

  • 1. A one-layer recurrent neural network with a discontinuous hard-limiting activation function for quadratic programming.
    Liu Q; Wang J
    IEEE Trans Neural Netw; 2008 Apr; 19(4):558-70. PubMed ID: 18390304
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A new one-layer neural network for linear and quadratic programming.
    Gao X; Liao LZ
    IEEE Trans Neural Netw; 2010 Jun; 21(6):918-29. PubMed ID: 20388594
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.
    Liu Q; Wang J
    IEEE Trans Neural Netw; 2011 Apr; 22(4):601-13. PubMed ID: 21402513
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A one-layer projection neural network for nonsmooth optimization subject to linear equalities and bound constraints.
    Liu Q; Wang J
    IEEE Trans Neural Netw Learn Syst; 2013 May; 24(5):812-24. PubMed ID: 24808430
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Solving quadratic programming problems by delayed projection neural network.
    Yang Y; Cao J
    IEEE Trans Neural Netw; 2006 Nov; 17(6):1630-4. PubMed ID: 17131675
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A class of finite-time dual neural networks for solving quadratic programming problems and its k-winners-take-all application.
    Li S; Li Y; Wang Z
    Neural Netw; 2013 Mar; 39():27-39. PubMed ID: 23334164
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A novel neural dynamical approach to convex quadratic program and its efficient applications.
    Xia Y; Sun C
    Neural Netw; 2009 Dec; 22(10):1463-70. PubMed ID: 19410427
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.
    Liu Q; Guo Z; Wang J
    Neural Netw; 2012 Feb; 26():99-109. PubMed ID: 22019190
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A recurrent neural network for solving nonlinear convex programs subject to linear constraints.
    Xia Y; Wang J
    IEEE Trans Neural Netw; 2005 Mar; 16(2):379-86. PubMed ID: 15787145
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A one-layer recurrent neural network for constrained nonsmooth optimization.
    Liu Q; Wang J
    IEEE Trans Syst Man Cybern B Cybern; 2011 Oct; 41(5):1323-33. PubMed ID: 21536534
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A novel recurrent neural network with finite-time convergence for linear programming.
    Liu Q; Cao J; Chen G
    Neural Comput; 2010 Nov; 22(11):2962-78. PubMed ID: 20804382
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A recurrent neural network with exponential convergence for solving convex quadratic program and related linear piecewise equations.
    Xia Y; Feng G; Wang J
    Neural Netw; 2004 Sep; 17(7):1003-15. PubMed ID: 15312842
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Neural network for solving convex quadratic bilevel programming problems.
    He X; Li C; Huang T; Li C
    Neural Netw; 2014 Mar; 51():17-25. PubMed ID: 24333480
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A one-layer recurrent neural network for constrained nonsmooth invex optimization.
    Li G; Yan Z; Wang J
    Neural Netw; 2014 Feb; 50():79-89. PubMed ID: 24292024
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints.
    Liu N; Qin S
    Neural Netw; 2019 Jan; 109():147-158. PubMed ID: 30419480
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A new gradient-based neural network for solving linear and quadratic programming problems.
    Leung Y; Chen KZ; Jiao YC; Gao XB; Leung KS
    IEEE Trans Neural Netw; 2001; 12(5):1074-83. PubMed ID: 18249935
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A high-performance feedback neural network for solving convex nonlinear programming problems.
    Leung Y; Chen KZ; Gao XB
    IEEE Trans Neural Netw; 2003; 14(6):1469-77. PubMed ID: 18244592
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints.
    Xia Y; Feng G; Wang J
    IEEE Trans Neural Netw; 2008 Aug; 19(8):1340-53. PubMed ID: 18701366
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Neurodynamic Optimization Approach to Bilevel Quadratic Programming.
    Qin S; Le X; Wang J
    IEEE Trans Neural Netw Learn Syst; 2017 Nov; 28(11):2580-2591. PubMed ID: 28113639
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An improved dual neural network for solving a class of quadratic programming problems and its k-winners-take-all application.
    Hu X; Wang J
    IEEE Trans Neural Netw; 2008 Dec; 19(12):2022-31. PubMed ID: 19054727
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.