Finding the collapse susceptible portion of a power system is one of the purposes of voltage stability analysis. This part which is a voltage control area is called the voltage weak area. Determining the weak area and adjecent voltage control areas has special importance in the improvement of voltage stability. Designing an on-line corrective control requires the voltage weak area to be determi...

Finding the collapse susceptible portion of a power system is one of the purposes of voltage stability analysis. This part which is a voltage control area is called the voltage weak area. Determining the weak area and adjecent voltage control areas has special importance in the improvement of voltage stability. Designing an on-line corrective control requires the voltage weak area to be determi...

Bankruptcy prediction is one of the major business classification problems. The main purpose of this study is to investigate Kohonen self-organizing feature map in term of performance accuracy in the area of bankruptcy prediction.  A sample of 108 firms listed in Tehran Stock Exchange is used for the study. Our results confirm that Kohonen network is a robust model for predicting bankruptcy in ...

The purpose of this study is to investigate handwritten online character recognition by Kohonen neural networks which learn class conditional Gibbs densities from training samples. The characters are represented by histograms (empirical distributions) of features. The Kohonen network learning algorithm implements a gradient ascent which maximizes an entropy criterion under constraints. Using a ...

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...

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 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...