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| Received:January 25, 2005Revised:April 14, 2005 |
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| Projection type neural network and its convergence analysis |
| Youmei LI, Feilong CAO |
| (Department of Computer Science, Shaoxing College of Arts and Sciences, Shaoxing Zhejiang 312000, China; China Jiliang University, Hangzhou Zhejiang 310018, China) |
| Abstract: |
| Projection type neural network for optimization problems has advantages over other networks for fewer parameters , low searching space dimension and simple structure. In this paper, by properly constructing a Lyapunov energy function, we have proven the global convergence of this network when being used to optimize a continuously differentiable convex function defined on a closed convex set. The result settles the extensive applicability of the network. Several numerical examples are given to verify the efficiency of the network. |
| Key words: Neural network Convex programming Global convergence Equilibrium points |