The Identification of Neurons Research

Abstract:

In view of the present medical neurons characteristic cognition and human brain plan in the neurons of the limitation of recognition, this paper puts forward the neurons identification method. First the L - Measure software to neuron geometry feature extraction, and then to extract high dimensional feature through the principal component analysis dimension reduction processing. Combined classifier with pyramidal neurons, general Ken wild neurons, motor neuron, sensory neurons, double neurons, level 3 neurons and multistage neurons 7 kinds of neurons are classified. Experimental results prove that the probabilistic neural network, the BP neural network, fuzzy classifier composed of classifier recognition effect is superior to the arbitrary single classifier.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 2813-2818
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.2813
• Online since: September 2013
• Authors: Xiao Jing Shang
• Keywords: Classification, Combined Classifier, L - Measure, Neurons, Principal Component Analysis (PCA), Recognition

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