### Abstract

A near-optimum parallel planarization algorithm is presented. The planarization algorithm, which is designed to embed a graph on a plane, uses a large number of simple processing elements called neurons. The proposed system, composed of an N×N neural network array (where N is the number of vertices), not only generates a near-maximal planar subgraph from a nonplanar graph or a planar graph but also embeds the subgraph on a single plane within 0(1) time. The algorithm can be used in multiple-layer problems such as designing printed circuit boards and routing very-large-scale integration circuits.

Original language | English |
---|---|

Pages (from-to) | 1221-1223 |

Number of pages | 3 |

Journal | Science |

Volume | 245 |

Issue number | 4923 |

Publication status | Published - 1989 |

Externally published | Yes |

### Fingerprint

### ASJC Scopus subject areas

- General

### Cite this

*Science*,

*245*(4923), 1221-1223.

**A near-optimum parallel planarization algorithm.** / Takefuji, Yoshiyasu; Lee, Kuo Chun.

Research output: Contribution to journal › Article

*Science*, vol. 245, no. 4923, pp. 1221-1223.

}

TY - JOUR

T1 - A near-optimum parallel planarization algorithm

AU - Takefuji, Yoshiyasu

AU - Lee, Kuo Chun

PY - 1989

Y1 - 1989

N2 - A near-optimum parallel planarization algorithm is presented. The planarization algorithm, which is designed to embed a graph on a plane, uses a large number of simple processing elements called neurons. The proposed system, composed of an N×N neural network array (where N is the number of vertices), not only generates a near-maximal planar subgraph from a nonplanar graph or a planar graph but also embeds the subgraph on a single plane within 0(1) time. The algorithm can be used in multiple-layer problems such as designing printed circuit boards and routing very-large-scale integration circuits.

AB - A near-optimum parallel planarization algorithm is presented. The planarization algorithm, which is designed to embed a graph on a plane, uses a large number of simple processing elements called neurons. The proposed system, composed of an N×N neural network array (where N is the number of vertices), not only generates a near-maximal planar subgraph from a nonplanar graph or a planar graph but also embeds the subgraph on a single plane within 0(1) time. The algorithm can be used in multiple-layer problems such as designing printed circuit boards and routing very-large-scale integration circuits.

UR - http://www.scopus.com/inward/record.url?scp=0037648004&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0037648004&partnerID=8YFLogxK

M3 - Article

VL - 245

SP - 1221

EP - 1223

JO - Science

JF - Science

SN - 0036-8075

IS - 4923

ER -