【摘要】 大脑是生物体内结构和功能最复杂的组织,其中包含上千亿个神经元。作为大脑构造的基本单位,神经元的结构和功能包含很多因素,其中神经元的几何形态特征就是一个重要方面。大脑中神经元的几何形态复杂多样,对其识别分类问题是一个难题。本文在模糊聚类的基础上根据神经元的几何形态建立了模糊集模型,并利用多数据库分类模型中的最优划分模型对模糊聚类分析法进行改进。将改进后的模糊聚类方法用于对神经元的识别分类,得到最优的分类结果。根据聚类的评价方法,与其他的聚类方法比较,证明了改进的模糊聚类方法能够得到更好的聚类效果。更多还原

【Abstract】 The brain is the most complex tissue in the structure and function of the organism,which contains hundreds of neurons.As a basic unit of the structure of the brain,the structure and function of neurons contain many factors,among which the geometric feature is an important aspect.The morphology of the neurons in brain is so complicated and diversiform that it is a problem to recognize the category of them.Here,we first establish the fuzzy set model based on fuzzy clustering according to the geometry of neurons.We use the optimal classification model of multi-database classification model to improve the fuzzy clustering method and classify the neurons.Then we can obtain the optimal classification result.According to the evaluation method of clustering,we can verify that the improved fuzzy clustering method can get better clustering effect compared with other methods.更多还原