The self-organizing map

Kohonen T.

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The self-organizing map

机译：自组织图

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摘要

The self-organized map, an architecture suggested for artificial neural networks, is explained by presenting simulation experiments and practical applications. The self-organizing map has the property of effectively creating spatially organized internal representations of various features of input signals and their abstractions. One result of this is that the self-organization process can discover semantic relationships in sentences. Brain maps, semantic maps, and early work on competitive learning are reviewed. The self-organizing map algorithm (an algorithm which order responses spatially) is reviewed, focusing on best matching cell selection and adaptation of the weight vectors. Suggestions for applying the self-organizing map algorithm, demonstrations of the ordering process, and an example of hierarchical clustering of data are presented. Fine tuning the map by learning vector quantization is addressed. The use of self-organized maps in practical speech recognition and a simulation experiment on semantic mapping are discussed.

机译：自组织图是为人工神经网络建议的体系结构，通过介绍模拟实验和实际应用来进行解释。自组织图具有有效创建输入信号各种特征及其抽象的空间组织内部表示的特性。其结果之一是自组织过程可以发现句子中的语义关系。审查了大脑图，语义图和有关竞争性学习的早期工作。回顾了自组织映射算法（一种在空间上对响应进行排序的算法），重点是最佳匹配单元格选择和权重向量的自适应。提出了应用自组织映射算法的建议，排序过程的演示以及数据分层聚类的示例。解决了通过学习矢量量化对地图进行微调的问题。讨论了自组织映射在实际语音识别中的应用以及语义映射的仿真实验。

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来源
《Proceedings of the IEEE》 |1990年第9期|P.1464-1480|共17页
作者
Kohonen T.;
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作者单位

Dept. of Comput. Sci., Helsinki Univ. of Technol., Espoo;

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原文格式 PDF
正文语种 eng
中图分类一般性问题;无线电电子学、电信技术;
关键词
learning systems; neural nets; self-adjusting systems; speech recognition; clustering; competitive learning; learning vector; neural networks; self-organizing map; semantic maps;

机译：学习系统;神经网络;自我调节系统;语音识别;聚类;竞争性学习;学习载体;神经网络;自组织图;语义图;

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专利

1. Comparison of visualization of optimal clustering using self-organizing map and growing hierarchical self-organizing map in cellular manufacturing system [J] . Chattopadhyay Manojit, Dan Pranab K., Mazumdar Sitanath Applied Soft Computing . 2014,第Null期

机译：自组织图和增长层次自组织图在蜂窝制造系统中最佳聚类可视化的比较
2. Representing and evaluating ultrasonic maps using active snake contours and Kohonen's self-organizing feature maps [J] . Kerem Altun, Billur Barshan Autonomous robots . 2010,第2期

机译：使用活动的蛇形轮廓和Kohonen的自组织特征图来表示和评估超声图
3. Representing and evaluating ultrasonic maps using active snake contours and Kohonen’s self-organizing feature maps [J] . Kerem Altun, Billur Barshan Autonomous Robots . 2010,第2期

机译：使用活动的蛇形轮廓和Kohonen的自组织特征图来表示和评估超声图
4. SOM of SOMs: Self-organizing Map Which Maps a Group of Self-organizing Maps [C] . Tetsuo Furukawa International Conference on Aritificial Neural Networks: Biological Inspirations(ICANN 2005) pt.1; 20050911-15; Warsaw(PL) . 2005

机译：SOM的儿子：映射一组自组织映射的自组织映射
5. A comparison of self-organizing maps and pathfinder networks for the mapping of co-cited authors. [D] . Buzydlowski, Jan William. 2003

机译：比较自组织地图和探路者网络以映射被引作者。
6. Application of Kohonens self-organizing feature map algorithm to cortical maps of orientation and direction preference [O] . N. V. Swindale, H.-U. Bauer 1998

机译：Kohonen的自组织特征图算法在取向和方向偏好的皮层图中的应用
7. SOM of SOMs: Self-organizing Map Which Maps a Group of Self-organizing Maps [O] . Furukawa Tetsuo 2005

机译：SOM的儿子：映射一组自组织映射的自组织映射

The self-organizing map

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