GeoEntropy: A measure of complexity and similarity

被引：25
|
作者：
Pham, Tuan D. [1 ]
机构：
[1] Univ New S Wales, Sch Engn & Informat Technol, Canberra, ACT 2600, Australia
来源：
PATTERN RECOGNITION | 2010年 / 43卷 / 03期
关键词：
Complexity; Similarity; Entropy; Geostatistics; Prediction; Classification; ENTROPY;
D O I：
10.1016/j.patcog.2009.08.015
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Measuring the complexity of a pattern expressed either in time or space has been introduced to quantify the information content of the pattern. which can then be applied for classification. Such information measures are particularly useful for the understanding of systems complexity in many fields of sciences, business and engineering. The novel concept of geostatistical entropy (GeoEntropy) as a measure of pattern complexity and similarity is addressed in this paper. It has been experimentally shown that GeoEntropy is an effective algorithm for studying signal predictability and has superior capability of classifying complex bio-patterns. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：887 / 896
页数：10
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