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Discrete-Time ZNN Algorithms for Time-Varying Quadratic Programming Subject to Time-Varying Equality Constraint

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7367)

Abstract

A special class of recurrent neural network (RNN), i.e., Zhang neural network (ZNN), has been proposed for a decade for solving online various time-varying problems. In this paper, we generalize and investigate a continuous-time ZNN model for online solution of the time-varying convex quadratic programming (QP) subject to a time-varying linear equality constraint. For the purpose of possible hardware (e.g., digital-circuit or digital-computer) realization, discrete-time ZNN models and numerical algorithms (i.e., discrete-time ZNN algorithms, in short) are proposed and developed by using Euler difference rules. Computer-simulation and numerical results demonstrate the efficacy and accuracy of the presented continuous-time ZNN model and the proposed discrete-time ZNN algorithms for solving online time-varying QP problems.

Keywords

  • Recurrent neural network (RNN)
  • Quadratic programming (QP)
  • Time-varying
  • Models
  • Discrete-time
  • Numerical algorithms

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References

  1. Zhang, Y., Li, Z.: Zhang neural network for online solution of time-varying convex quadratic program subject to time-varying linear-equality constraints. Physics Letters A 373(18-19), 1639–1643 (2009)

    CrossRef  MATH  Google Scholar 

  2. Zhang, Y., Ruan, G., Li, K., Yang, Y.: Robustness analysis of the Zhang neural network for online time-varying quadratic optimization. Journal of Physics A: Mathematical and Theoretical 43, 245202 (2010)

    CrossRef  MathSciNet  Google Scholar 

  3. Zhang, Y., Yi, C.: Zhang Neural Networks and Neural-Dynamic Method. Nova Science Publishers, New York (2011)

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  4. The MathWorks, Inc.: MATLAB 7.0. Natick, MA (2004)

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© 2012 Springer-Verlag Berlin Heidelberg

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Ke, Z., Yang, Y., Zhang, Y. (2012). Discrete-Time ZNN Algorithms for Time-Varying Quadratic Programming Subject to Time-Varying Equality Constraint. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_6

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  • DOI: https://doi.org/10.1007/978-3-642-31346-2_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31345-5

  • Online ISBN: 978-3-642-31346-2

  • eBook Packages: Computer ScienceComputer Science (R0)