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It is fundamental work to translate the historical characters called "kuzushi-ji" into the contemporary characters in Japanese historical studies. In this paper, we develop the Japanese historical character recognition system using the directional element features and modular neural networks. Modular neural networks consist of two kinds of classifiers: a rough classifier to find the several...
The self-organizing map that Kohonen has proposed maps high-dimensional vector data to low-dimensional space by phase conservation. And, it generates the feature map that visually catches the similarity among data. In addition, the reference vector where the unit in a competitive layer of SOM is achieved can interpolate an intermediate vector of the input vector data. In the pattern recognition of...
This paper describes how recursive nodes with rich dynamics can be explored in a self-organizing artificial network for continuous learning tasks. The purpose of inserting the recursive elements is introducing chaos behavior in a modified self-organizing map (SOM). This new structure is called CSOM. It incorporates some of the main features of SOM, but it also improves the capability of cluster input...
In this paper we propose a method to implement SOM neural network in FPGA circuits: a self organized map neural network with on-chip learning algorithm. The method implies the building of a neural network by generic blocks designed in Mathworks' Simulink environment. The main characteristics of this solution are onchip learning algorithm implementation and high reconfiguration capability and operation...
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