in this paper we address the issue of recognizing farsi handwritten words. two types of gradient features are extracted from a sliding vertical stripe which sweeps across a word image. these are directional and intensity gradient features. the feature vector extracted from each stripe is then coded using the self organizing map (som). in this method each word is modeled using the discrete hidde...

abstract this paper presents a robust approach using artificial neural networks in the form of a self organizing map (som) as a semi-automatic method for analysis and identification of morphometric features in two completely different environments, the man and biosphere reserve “eastern carpathians” (central europe) in a complex mountainous humid area and yardangs in lut desert, iran, a hyper a...

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 ...