On the simplified LVI-based primal-dual neural Network for solving LP and QP problems

2007 IEEE International Conference on Control and Automation, ICCA

Volumn , Issue , 2007, Pages 3129-3134

  Zhang, Yunong ^a   Li, Zhonghua ^a   Tan, Hong Zhou ^a   Fan, Zhengping ^a  

^a SUN YAT SEN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; LINEAR PROGRAMMING; QUADRATIC PROGRAMMING; REAL TIME SYSTEMS;

BOUND CONSTRAINTS; GLOBAL CONVERGENCE;

NEURAL NETWORKS;

EID: 44349181369     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCA.2007.4376938     Document Type: Conference Paper

References (24)

1. Y. Zhang, Analysis and Design of Recurrent Neural Networks and Their Applications to Control and Robotic Systems, Ph.D. Thesis, Chinese University of Hong Kong, 2002.
2. Y. Zhang, "Minimum-energy redundancy resolution unified by quadratic programming," The 15th International Symposium on Measurement and Control in Robotics, 2005.
3. Y. Zhang, "On the LVI-based primal-dual neural network for solving online linear and quadratic programming problems," Proceedings of American Control Conference, pp. 1351-1356, 2005.
4. T. L. Friesz, D. H. Bernstein, N. J. Mehta, R. L. Tobin, and S. Ganjlizadeh, "Day-to-day dynamic network disequilibria and idealized traveler information systems," Operations Research, vol 42, pp. 1120-1136, 1994.
5. D. W. Tank and J. J. Hopfield, "Simple neural optimization networks: an A/D converter, signal decision circuit, and a linear programming circuit," IEEE Transaction on Circuits and Systems, vol. 33, pp. 533-541, 1986.
6. A. Cichocki and R. Unbehauen, Neural Networks for Optimization and Signal Processing, U. K.: Wiley, London, England, 1993.
7. Y. Zhang, "Towards piecewise-linear primal neural networks for optimization and redundant robotics," Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control pp. 374-379, 2006.
8. C. Mead, Analog VLSI and Neural Systems, Reading, Mass.: Addison-Wesley, 1989.
9. N. M. Botros and M. Abdul-Aziz, "Hardware implementation of an artificial neural network using field programmable gate arrays (FPGAs)," IEEE Transactions on Industrial Electronics, vol. 41, no. 6, pp. 665-667, 1994.
10. C. Diorio and R. P. N. Rao, "Neural circuits in silicon," Nature, vol. 405, no. 6789, pp. 891-892, 2000.
11. Y. Zhang, "Revisit the analog computer and gradient-based neural system for matrix inversion," Proceedings of IEEE International Symposium on Intelligent Control, pp. 1411-1416, 2005.
12. Y. Zhang and J. Wang, "A dual neural network for convex quadratic programming subject to linear equality and inequality constraints," Physics Letters A, vol. 298, pp. 271-278, 2002.
13. M. P. Kennedy and L. O. Chua, "Neural networks for nonlinear programming," IEEE Transactions on Circuits and Systems, vol. 35, no. 5, pp. 554-562, 1988.
14. S. Zhang and A. G. Constantinides, "Lagrange Programming Neural Networks," IEEE Transactions on Circuits and Systems, vol. 39, no. 7, pp. 441-452, 1992.
15. D. Gong, M. Gen, G. Yamazaki, and W. Xu, "A modified ANN for convex programming with linear constraints," Proceedings of IEEE International Conference on Neural Networks, vol. 1, pp. 537-542, 1996.
16. W. S. Tang and J. Wang, "A primal-dual neural network for kinematic control of redundant manipulators subject to joint velocity constraints," Proceedings of the 6th International Conference on Neural Information Processing, vol. 2, pp. 801-806, 1999.
17. Y. Zhang, S. S. Ge, and T. H. Lee, "A unified quadratic programming based dynamical system approach to joint torque optimization of physically constrained redundant manipulators," IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 34, no. 5, pp. 2126-2133, 2004.
18. Y. Xia and J. Wang, "A recurrent neural network for solving linear projection equations," Neural Networks, vol. 13, no. 3, pp. 337-350, 2000.
19. B. He, "A projection and contraction method for a class of linear complementarity problems and its application in conves quadratic programming," Applied Mathematics and Optimization, vol. 25, pp. 247-262, 1992.
20. B. He and H. Yang, "A neural network model for monotone linear asymmetric variational inequalities," IEEE Transactions on Neural Networks, vol. 11, no. 1, pp. 3-16, 2000.
21. M. Fukushima, "Equivalent differentiable optimization problems and descent method for asymmetric variational inequality problems," Math. Programming, vol. 53, pp. 99-110, 1992.
22. X.-B. Liang, "On the analysis of a recurrent neural network for solving nonlinear monotone variational inequality problems," IEEE Transactions on Neural Networks, vol. 13, no. 2, pp. 481-486, 2002.
23. X.-B. Gao, "Exponential stability of globally projected dynamic systems," IEEE Transactions on Neural Networks, vol. 14, no. 2, pp. 426-431, 2003.
24. Y. Xia and G. Feng, "On convergence rate of projection neural networks," IEEE Transactions on Automatic Control vol. 49, no. 1, pp. 91-96, 2004.