A Neuron Classifier Based on Support Vector Machine and Fractal Geometry

被引：0

作者：

Han, Fengqing ^{[1
]}

Zeng, Jie ^{[2
]}

Zhang, Duo ^{[1
]}

机构：

[1] Chongqing Jiaotong Univ, Sch Sci, Chongqing, Peoples R China

[2] Chongqing Jiaotong Univ, Dept Comp Applicat Technol, Chongqing, Peoples R China

来源：

ISBE 2011: 2011 INTERNATIONAL CONFERENCE ON BIOMEDICINE AND ENGINEERING, VOL 3 | 2011年

关键词：

Support Vector Machine; Fractal Geometry; Spatial Structure of Neurons; Classification of Neurons;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper, a method is proposed for neurons classifying based on support vector machines and fractal dimension. The part of neuron is geometrically similar to the whole. Neurons can be regarded as fractal. Different types of neurons fill with different levels in space. So, their fractal dimensions are also different. First, fractal dimensions are calculated for the different types of neurons. Then the other 16 spatial structure indicators are added in the classifier. There are 44 neurons as the training samples to train Support Vector Machine and other 20 neurons as the test samples. Experiments show that the correct classification rate is almost over 70% for many cases. It provides a new method to classify neurons.

引用

页码：435 / 438

页数：4