Optimal solution to crossbar packet-switch problems using a sequential binary Hopfield neural network

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• 作者：Sancho Salcedo-Sanz ; Jose A. Portilla-Figueras
• 刊名：Neurocomputing
• 出版年：2007
• 出版时间：August 2007
• 年：2007
• 卷：70
• 期：13-15
• 页码：2603-2607
• 全文大小：209 K

文摘

In this paper a sequential binary Hopfield network architecture to solve crossbar switch problems (CSP) is proposed. It is shown that the sequential Hopfield algorithm's performance on the CSP depends on the neurons’ updating ordering, and also an optimal ordering for the CSP is proposed. Our sequential binary Hopfield network has been applied to the resolution of large and very large CSP instances, obtaining optimal solutions within less steps than previous approaches to this problem.