Abstract
In this paper, a projection neural network for solving convex optimization is investigated. Using Lyapunov stability theory and LaSalle invariance principle, the proposed network is showed to be globally stable and converge to exact optimal solution. Two examples show the effectiveness of the proposed neural network model.
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Yang, Y., Xu, X. (2007). The Projection Neural Network for Solving Convex Nonlinear Programming. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_20
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DOI: https://doi.org/10.1007/978-3-540-74205-0_20
Publisher Name: Springer, Berlin, Heidelberg
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