Four self-organizing neural networks are compared for automatic deinterleaving of radar pulse streams in electronic warfare systems. The neural networks are the Fuzzy Adaptive Resonance Theory, Fuzzy Min-Max Clustering, Integrated Adaptive Fuzzy Clustering, and Self-Organizing Feature Mapping. Given the need for a clustering procedure that ooers both accurate results and computational eeciency,...

This work presents a neural network model for the clustering analysis of data based on Self Organizing Maps (SOM). The model evolves during the training stage towards a hierarchical structure according to the input requirements. The hierarchical structure symbolizes a specialization tool that provides refinements of the classification process. The structure behaves like a single map with differ...

purpose: this study aims to assess the information seeking behavior of medical science university researchers using neural network in khorasan razavi. methodology: the study is an applied and descriptive survey which is conducted through the quantitative approach using neural networks.the data were collected through the questionnaire to examine the information seeking behavior of medical scienc...

The semantic of neural networks is not explicit and they are considered as black box systems. There are many researches investigating the area of rule extraction by neural networks. In this paper, the eclectic approach of rule extraction from a dynamic cell structure (DCS) neural network is investigated. To do this, a modified version of LERX algorithm is used for rule generation. Empirical res...

The reasons to use growing self-organizing networks are investigated. First an overview of several models of this kind is given are they are related to other approaches. Then two examples are presented to illustrate the speci c properties and advantages of incremental networks. In each case a non-incremental model is used for comparison purposes. The rst example is pattern classi cation and com...

BACKGROUND The range of the fatty acids has been largely investigated in the plasma and erythrocytes of patients suffering from neuropsychiatric disorders. In this paper we investigate, for the first time, whether the study of the platelet fatty acids from such patients may be facilitated by means of artificial neural networks. METHODS Venous blood samples were taken from 84 patients with a D...

The method of self-organizing maps (SOM) is a method of exploratory data analysis used for clustering and projecting multi-dimensional data into a lower-dimensional space to reveal hidden structure of the data. The Self-Organizing Feature Maps (SOFMs) [11] is a class of neural networks capable of recognizing the main features of the data they are trained on. There is extensive literature on its...

A new dynamic systems modeling approach, based on self-organizing neural networks, is presented. An adaptive control strategy that utilizes this modeling method is proposed, and it is experimented in the control of a pH process plant.

A colour quantization technique is presented which maps 24-bit colour images to 8bit colour, using Self-Organizing Neural Networks. The quantized image is superior to that produced by existing methods, and has useful continuity properties.