An algorithm for multi-layer channel routing problem using chaotic neural networks

2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353) Pub Date : 2000-05-28 DOI:10.1109/ISCAS.2000.857385

M. Ohta

引用次数: 2

Abstract

In this paper a novel algorithm for the multi-layer channel routing problem in VLSI design using a chaotic neural network (chaotic NN) is proposed. For this problem, Funabiki and Takefuji (1992) proposed a parallel algorithm using the maximum neural network. However it is often caught in a local minimum because the maximum neural network is based on the Hopfield neural network. On the other hand, the chaotic NN has the characteristic of escaping from a local minimum. A novel algorithm using the chaotic NN is proposed. In order to confirm the effectiveness of the algorithm, numerical experiments are carried out, and it is confirmed experimentally that the proposal is more effective than the Funabiki and Takefuji algorithm.

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基于混沌神经网络的多层信道路由算法

本文提出了一种利用混沌神经网络(chaotic neural network，简称混沌神经网络)解决VLSI设计中多层信道路由问题的新算法。对于这个问题，Funabiki和Takefuji(1992)提出了一种利用最大神经网络的并行算法。然而，由于极大值神经网络是基于Hopfield神经网络的，它经常陷入局部极小值。另一方面，混沌神经网络具有摆脱局部极小值的特性。提出了一种新的混沌神经网络算法。为了验证算法的有效性，进行了数值实验，实验证实了该算法比Funabiki和Takefuji算法更有效。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)

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