吉林大学学报（信息科学版）2011，Vol.29Issue(3)：237-244,8.
神经元的几何形态分类
Geometry Morphological Classification of Neurons
摘要
Abstract
In order to disytiguish different nellrons, the morphological classification of neurons in the understanding of the characteristics of neuron structure and function has great significance. Using L-Measure software to extract geometry of neurons for feature, characteristics extracted through principal component analysis to reduce the dimension. Using probabilistic neural network, BP ( Back Propagation) neural network, fuzzy classifier consisting of "Note" on the pyramidal neurons, purkinje neuron, motor neurons, sensory neurons, Bipolar inter-neuron , tripolar interneuron and multipolar interneuron to classify 7 kinds of neuron. Experiments show that the classification of three combined is better than any of them has good performance, a higher recognition rate.关键词
神经元/概率神经网络/BP神经网络/模糊分类器/投票分类Key words
neurons/probabilistic neural network/BP neural network/fuzzy classifier/voting classification分类
计算机与自动化引用本文复制引用
尚小晶,刘小梅,李成凤,李阳,田彦涛..神经元的几何形态分类[J].吉林大学学报（信息科学版）,2011,29(3):237-244,8.基金项目
吉林省科技发展重点基金资助项目(20090350) （20090350）
中国高校博士专项科研基金资助项目(20100061110029) （20100061110029）
吉林大学博士生交叉学科科研资助计划基金资助项目(2011J009) （2011J009）
