The purpose of this study is to investigate a method for high performance on-line Arabic characters recognition. This method is based on the use of Kohonen maps and their corresponding confusion matrices which serve to prune them of error-causing nodes, and to combine them consequently. We use two Kohonen maps obtained using two distinct character representations, namely, Fourier descriptors an...

This article presents the Kohonen network application in the speech analysis. The Authors have modified the traditional Kohonen network learning process like weights initialization, neurons reduction and neurons sorting. The results will be presented using authors’ program – “WaveBlaster”.

We present an implementation of Kohonen Self-Organizing Feature Maps for the Spert-II vector microprocessor system. The implementation supports arbitrary neural map topologies and arbitrary neighborhood functions. For small networks, as used in real-world tasks, a single Spert-II board is measured to run Kohonen net classiication at up to 208 million connections per second (MCPS). On a speech c...

We develop an unsupervised “dual-network” connectionist model of category learning in which rules gradually emerge from a standard Kohonen network. The architecture is based on the interaction of a statistical-learning (Kohonen) network and a competitive-learning rule network. The rules that emerge in the rule network are weightings of individual features according to their importance for categ...

Kohonen clustering is one of the important functions of data mining. From the aspect of data mining, clustering research extracts valuable knowledge from large data sets intelligently and automatically. Kohonen clustering was proposed along with the development of databases and the emergence of data mining and Knowledge discovery technology. Kohonen clustering is applied in many areas, such as:...

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...

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 ...

La propuesta de un modelo espacio-temporal y red neuronal artificial Kohonen mapas autoorganizados para la investigación documental descriptiva, pronostica el volumen monetario ARIMA del Producto Interno Bruto, Exportaciones e Importaciones período 2020-2022 en millones soles 94,540; 21,184 24,827. Evidenciando error porcentual absoluto MAPE 4,22%; 7,45% 5,54% diciembre 2022, ajuste significati...

1. INTRODUCTION Self-organizing neural networks represent a family of useful clustering-based classification methods in several application domains. One such technique is the Kohonen Self-Organizing Feature Map (SOM) (Kohonen,