2002年3月
An efficient parallel algorithm for planarization problem
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
- ,
- ,
- 巻
- 49
- 号
- 3
- 開始ページ
- 397
- 終了ページ
- 401
- 記述言語
- 英語
- 掲載種別
- DOI
- 10.1109/81.989179
- 出版者・発行元
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
A parallel algorithm for solving the planarization problem using a gradient ascent learning of Hopfield network is presented. This algorithm which is designed to embed a graph on a plane, uses the Hopfield neural network to get a near-maximal planar subgraph, and increase the energy by modifying weights in a gradient ascent direction to help the network escape from the state of the near-maximal planar subgraph to the state of the maximal planar subgraph or better one. The proposed algorithm is verified by a large number of simulation runs and compared with other parallel algorithms for the planarization problem. The experimental results show that the proposed algorithm can generate as good as or better solutions than the other existing parallel algorithm for the planarization problem.
- リンク情報
- ID情報
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- DOI : 10.1109/81.989179
- ISSN : 1549-8328
- eISSN : 1558-0806
- Web of Science ID : WOS:000174270700021