In this paper, we propose a Kohonen feature map associative memory with area representation for sequential patterns. This model is based on the Kohonen feature map associative memory with area representation and the Kohonen feature map associative memory for temporal sequences. The proposed model can learn sequential patterns successively, and has robustness for damaged neurons. We carried out ...

A self-organizing neural network for sequence classification called SARDNET is described and analyzed experimentally. SARDNET extends the Kohonen Feature Map architecture with activation retention and decay in order to create unique distributed response patterns for different sequences. SARDNET yields extremely dense yet descriptive representations of sequential input in very few training itera...

Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear debris analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self-organizing maps. This is achieved using relationship measurements...

We seek to implement intelligent character recognition of handwritten equations in a manner that allows for a computer program to translate a user’s hand-drawn equation into formatted LTEX. We use a Kohonen neural network fed by downsampled images to accomplish this task. While we were able to achieve single-character recognition with a very low error rate, multiple character recognition and wh...

This article presents a hybrid approach for texture-based image classification using the gray-level co-occurrence matrices (GLCM) and a new Fuzzy Kohonen Clustering Network for Symbolic Interval Data (IFKCN). The GLCM matrices extracted from an image database are processed to create the training data set using IFKCN algorithm. The IFKCN organizes and extracts prototypes from processed GLCM matr...

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...

Each two years, the “Workshop on Self-Organizing Maps” (WSOM) covers the new developments in the field. The WSOM series of conferences was initiated in 1997 by Prof. Teuvo Kohonen, and has been successfully organized in 1997 and 1999 by the Helsinki University of Technology, in 2001 by the University of Lincolnshire and Humberside, and in 2003 by the Kyushu Institute of Technology. The Universi...

For unmanned electric drive chassis parameter optimization problems, an model containing power systems and energy was built using CRUISE, as the traditional genetic algorithm is prone to falling into local optima, improved isolation niche based on KOHONEN network clustering (KIGA) proposed. The simulation results show that proposed KIGA can reasonably divide initial populations. Compared with (...