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A self-organizing network with fuzzy hyperellipsoidal classifying and its application in handwritten numeral recognition

机译:具有模糊超椭球分类的自组织网络及其在手写数字识别中的应用

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This paper proposes a self-organizing network with the fuzzy hyperellipsoid-classifier (FHECFN) and utilizes it to recognize handwritten numerals. Based on the clustering result of SOM, FHECFN divides the center that performs worse taking the advantage of the fuzzy hyperellipsoidal clustering algorithm. When reaching the satisfying requirement, the network stops divining and then obtains the suitable number of prototypes and the hyperellipsoidal classifying result. With the supervised learning algorithm, such as learning vector quantization, the network achieves a better learning result and in the experiments of recognizing the handwritten numerals, the network shows a promising performance.
机译:本文提出了一种具有模糊超椭球分类器(FHECFN)的自组织网络,并利用它来识别手写数字。基于SOM的聚类结果,FHECFN利用模糊超椭球聚类算法对性能较差的中心进行划分。当达到满意的要求时,网络停止占卜,然后获得合适数量的原型和超椭球分类结果。借助学习向量量化等有监督的学习算法,该网络获得了更好的学习效果,并且在识别手写数字的实验中,该网络表现出了令人鼓舞的性能。

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