Abstract
This paper presents an efficient approach based on Hopfield network for solving nonlinear optimization problems, with polynomial objective function, polynomial equality constraints and polynomial inequality constraints. A modified Hopfield network is developed and its stability and convergence is analyzed in the paper. Then a mapping of nonlinear optimization problems is formulated using the modified Hopfield network. Simulation results are provided to demonstrate the performance of the proposed neural network.
This research work is supported by the Natural Science Fund of China ( # 70501022).
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Yu, C., Luo, Y. (2007). A Modified Hopfield Network for Nonlinear Programming Problem Solving. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_39
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DOI: https://doi.org/10.1007/978-3-540-72395-0_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72394-3
Online ISBN: 978-3-540-72395-0
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