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A new class of interval projection neural networks for solving interval quadratic program

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  • Ding, Ke
  • Huang, Nan-Jing

Abstract

In this paper, a new class of interval projection neural networks are introduced and studied, the equilibrium point of this neural networks is equivalent to the KT point of a class of interval quadratic program. By using fixed point theorem and constructing suitable Lyapunov functions, we obtain sufficient conditions to ensure the existence and global exponential stability for the unique equilibrium point of interval projection neural networks. In the last section, we give an example to illustrate the validity of our results.

Suggested Citation

  • Ding, Ke & Huang, Nan-Jing, 2008. "A new class of interval projection neural networks for solving interval quadratic program," Chaos, Solitons & Fractals, Elsevier, vol. 35(4), pages 718-725.
    • Handle: RePEc:eee:chsofr:v:35:y:2008:i:4:p:718-725
    DOI: 10.1016/j.chaos.2006.05.037
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    References listed on IDEAS

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    1. Terry L. Friesz & David Bernstein & Nihal J. Mehta & Roger L. Tobin & Saiid Ganjalizadeh, 1994. "Day-To-Day Dynamic Network Disequilibria and Idealized Traveler Information Systems," Operations Research, INFORMS, vol. 42(6), pages 1120-1136, December.
    2. Li, Chuandong & Liao, Xiaofeng & Zhang, Rong & Prasad, Ashutosh, 2005. "Global robust exponential stability analysis for interval neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 25(3), pages 751-757.
    3. Zhang, Hongbin & Li, Chunguang & Liao, Xiaofeng, 2005. "A note on the robust stability of neural networks with time delay," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 357-360.
    4. Y. S. Xia, 2004. "Further Results on Global Convergence and Stability of Globally Projected Dynamical Systems," Journal of Optimization Theory and Applications, Springer, vol. 122(3), pages 627-649, September.
    5. Y. S. Xia & J. Wang, 2000. "On the Stability of Globally Projected Dynamical Systems," Journal of Optimization Theory and Applications, Springer, vol. 106(1), pages 129-150, July.
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    Cited by:

    1. Ammar, E.E., 2009. "On fuzzy random multiobjective quadratic programming," European Journal of Operational Research, Elsevier, vol. 193(2), pages 329-341, March.
    2. Wu, Zeng-bao & Zou, Yun-zhi & Huang, Nan-jing, 2016. "A class of global fractional-order projective dynamical systems involving set-valued perturbations," Applied Mathematics and Computation, Elsevier, vol. 277(C), pages 23-33.
    3. Jin-dong Li & Nan-jing Huang, 2018. "Asymptotical Stability for a Class of Complex-Valued Projective Neural Network," Journal of Optimization Theory and Applications, Springer, vol. 177(1), pages 261-270, April.
    4. Lan, Heng-you & Cui, Yi-Shun, 2009. "A neural network method for solving a system of linear variational inequalities," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1245-1252.

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