Research for Neuron Classification Based on Support Vector Machine

In this paper, a new method is proposed for neurons classifying based on its spatial structure. 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 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.