A study on Two-stage self-organizing map suitable for clustering problems

被引：0

作者：

Kato, Satoru ^{[1
]}

Koike, Kenta ^{[2
]}

Horiuchi, Tadashi ^{[1
]}

Itoh, Yoshio ^{[3
]}

机构：

[1] Matsue Natl Coll Technol, Matsue, Shimane 6908518, Japan

[2] Crestron Japan Co, Matsue, Shimane 6900011, Japan

[3] Tottori Univ, Tottori 6808552, Japan

来源：

2006 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATIONS, VOLS 1 AND 2 | 2006年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a two-stage self-organizing map algorithm what we call Two-stage SOM which combines Kohonen's basic SOM (BSOM) and Aoki's SOM with threshold operation (THSOM). In the first stage of Two-stage SOM, we use BSOM algorithm in order to acquire topological structure of input data, and then we apply THSOM algorithm so that inactivated code-vectors move to appropriate region reflecting the distribution of the input data. Furthermore, we show that Two-stage SOM can be applied to clustering problems. Some experimental results reveal that Two-stage SOM is effective for clustering problems in comparison with conventional methods.

引用

页码：620 / +

页数：2

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