A CLUSTER DETECTION ALGORITHM BASED ON PERCOLATION THEORY

被引：6

作者：

GOTSMAN, C

机构：

[1] Dept. of Computer Science, The Hebrew University, Jerusalem

来源：

PATTERN RECOGNITION LETTERS | 1991年 / 12卷 / 04期

关键词：

CLUSTER; PERCOLATION; RANDOM GRAPH; POISSON PROCESS;

D O I：

10.1016/0167-8655(91)90032-H

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We describe a novel algorithm for the detection of clusters of points embedded in background noise in the plane. The algorithm is based on the percolation phenomena found in random graphs obtained from a planar Poisson process. We estimate the time complexity of the algorithm and its expected performance.

引用

页码：199 / 202

页数：4

共 12 条

[1]

BERGER JR, 1990, IN PRESS J ALGORITHM

[2] DETECTION OF DIFFUSE CLUSTERS IN NOISE BACKGROUND [J].