Use of neural nets in channel routing

Fujii,; Tenorio,; Zhu, Wanxue

doi:10.1109/ijcnn.1989.118603

Cited by 8 publications

(1 citation statement)

References 14 publications

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“…While the primary research interests in neural network are concentrated in the information processing and biological modeling [14], it has been shown that neural network also can collectively compute good solutions to complex optimization problems [4,5,10,16,17]. This approach comes from the observation that the dynamics of the network will force the network to converge to a minimal energy state [8,9].…”

Section: Overview On Neural Network For Optimizationmentioning

confidence: 99%

Neural networks for vertical microcode compaction

Chu

1992

SPIE Proceedings

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Neural networks provide an alternative way to solve complex optimization problems. Instead of performing a program of instructions sequentially as in a traditional corn-. puter, neural network model explores many competing hypotheses simultaneously using its massively parallel net. The paper shows how to use neural network approach to perform vertical micro-code compaction for a micro-programmed control unit. The compaction procedure includes two basic steps. The first step determines the compatibility classes and the second step selects a minimal subset to cover the control signals. Since the selection process is an NP-complete problem, to find an optimal solution is impractical. In this study, we employ a customized neural network to obtain the minimal subset. We first formalize this problem, and then define an "energy function" and map it to a two-layer fully-connected neural network. The modified network has two types of neurons and can always obtain a valid solution.

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