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Neural Networks having the Time-variant Connection for Multi-layer Channel Routing Problem

机译:具有时间变量连接的神经网络,用于多层信道路由问题

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It is necessary for designing VLSI to arrange wirings not to overlap each other in the wiring area of a layer. The problem to find such arrangement is called multi-layer channel routing problem. This article proposes the neural networks having the time-variant connection for such problem. In previous studies, a monotonously decreasing energy function is introduced into the system. Therefore, the system operates toward the minimum of the energy. Then, to find the optimum solution, this minimum corresponds to the minimum of the cost function. However, this method hardly finds the optimum solution if the energy function has many local minima. On the other hand, higher order connection system is scarcely influenced by local minima to find the solution. It takes, however, the system so long time to find the solution. Then, in this article, the time-variant connection system is proposed to find the solution quickly without the influence of local minima.
机译:有必要设计VLSI,以在图层的布线区域中排列不彼此重叠的布线。找到这种安排的问题称为多层信道路由问题。本文提出了具有用于此类问题的时变连接的神经网络。在先前的研究中,将单调的能量函数引入系统中。因此,该系统朝向最低能量运行。然后,为了找到最佳解决方案,该最小值对应于成本函数的最小值。然而,如果能量函数有许多局部最小值,这种方法几乎没有找到最佳解决方案。另一方面,高阶连接系统几乎受到当地最小值的影响,以找到解决方案。然而,它需要很长时间找到解决方案。然后,在本文中,提出了时变连接系统以快速找到解决方案而不会影响局部最小值的影响。

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