Understanding Kohonen Networks
نویسنده
چکیده
Kohonen neural nets are some kind of competitive nets. The most commonly known variants are the Self-Organizing Maps (SOMs) and the Learning Vector Quantization (LVQ). The former model uses an unsupervized learning, the latter is an e cient classi er. This paper tries to give, in simple words, a clear idea about the basis of competitive neural nets and competitive learning emphasizing on the SOMs and some of their real-world applications. It should not be considered as an exhaustive reference but as a simple introductory.
منابع مشابه
An Unsupervised Learning Method for an Attacker Agent in Robot Soccer Competitions Based on the Kohonen Neural Network
RoboCup competition as a great test-bed, has turned to a worldwide popular domains in recent years. The main object of such competitions is to deal with complex behavior of systems whichconsist of multiple autonomous agents. The rich experience of human soccer player can be used as a valuable reference for a robot soccer player. However, because of the differences between real and simulated soc...
متن کاملNeural Networks Applied to Spatial Load Forecasting in GIS
Quality spatial load forecasting is a major prerequisite for energy distribution systems planning. The load evolution outline depends on the urban expansion and its land usage. This paper presents a methodology for knowledge extraction of the data provided by a GIS (Geographical Information Systems) platform. The main goal consists of developing studies that lead to the understanding of the inf...
متن کاملCompression of Medical Images using Improved Kohonen Algorithm
Nowadays, neural networks are largely used in signal processing and images. In particular, Kohonen networks or Self Organizing Maps are unsupervised learning models. This method performs a vector quantization (VQ) on the values obtained after processing. The vector quantization has a potential to give more data compression maintaining the same quality. In this paper we propose new scheme to ima...
متن کاملDesign of Kohonen Self-organizing Map with Reduced Structure
This paper deals with design of optimal structure of Kohonen Self-organizing maps for cluster analysis applications. The cluster analysis represents a group of methods whose aim is to classify the objects into clusters. There have been many new algorithms solving cluster analysis applications, which used neural networks. This paper deals with the use of advanced methods of neural networks repre...
متن کاملKohonen Networks with Graph-based Augmented Metrics
Correct and efficient text classification is a major challenge in today’s world of rapidly increasing amount of accessible electronic text data. Kohonen networks have been applied to document classification with comparable success to other document clustering methods. An important challenge is to devise text similarity metrics that can improve the performance of text classification Kohonen netw...
متن کاملImproved Self-Organizing Maps and Speech Compression
Recent developments of Self-Organizing Maps or Kohonen networks become more and more interesting in many fields such as: pattern recognition, clustering, speech recognition, data compression, medical diagnosis... Kohonen networks is unsupervised learning models. The results obtained by the Kohonen networks are dependent on their parameters such as the architecture of the Kohonen map, the later ...
متن کامل