The parameterless self-organizing map algorithm

被引：84
|
作者：
Berglund, E [1 ]
Sitte, J
机构：
[1] Univ Queensland, Div Complex & Intelligent Syst, St Lucia, Qld 4072, Australia
[2] Queensland Univ Technol, Smart Devices Lab, Brisbane, Qld 4001, Australia
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 2006年 / 17卷 / 02期
关键词：
self-organizing feature maps;
D O I：
10.1109/TNN.2006.871720
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The parameterless self-organizing map (PLSOM) is a new neural network algorithm based on the self-organizing map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighborhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM performs satisfactory. Finally we discuss some example applications of the PLSOM and present a proof of ordering under certain limited conditions.
引用
收藏
页码：305 / 316
页数：12
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