Channel routing: Efficient solutions using neural networks

作者: Taj-ul Islam

DOI:

关键词: Stochastic neural networkBenchmark (computing)Routing (electronic design automation)Rate of convergenceInterval graphArtificial neural networkComputer scienceAlgorithmCellular neural networkComputer networkTime delay neural network

摘要: Neural network architectures are effectively applied to solve the channel routing prob lem. Algorithms for both two-layer and multilayer channel-width minimization, constrained via minimization proposed implemented. Experimental results show that algorithms much superior in all respects compared existing algorithms. The optimal solutions most of benchmark problems, not previously obtained, obtained first time, including an solution famous Deutch's difficult problem. four-layers one be lchmark is time. Both convergence rate speed with which simulations executed outstanding. A neural problem also presented. In addition, a fast simple linear-time algorithm presented, possibly coloring vertices interval graph, provided line intervals given.

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