[1]XU Shao-hua,LI Pan-chi,HE Xin-gui.Combined probabilistic process neural network and classification algorithm[J].CAAI Transactions on Intelligent Systems,2009,4(4):283-287.
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Combined probabilistic process neural network and classification algorithm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 4 Page number: 283-287 Column: 学术论文—机器学习 Public date: 2009-08-25
Title:
Combined probabilistic process neural network and classification algorithm
Author(s):
XU Shao-hua1; 2;  LI Pan-chi1;  HE Xin-gui2
1. School of Computer and Information Technology, Daqing Petroleum Institute, Daqing 163318, China;
2. School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
Keywords:
dynamic signal classification;  Bayesian rules;  probabilistic process neural networks
CLC:
TP183
DOI:
-
Abstract:
A probabilistic process neural network has been proposed in order to provide integration of a priori knowledge with dynamic information classification. In this model, Bayesian classification was combined with the dynamic information processing of process neural networks. Dynamic information classification based on Bayesian rules was realized by adding a pattern neuron layer and a summing neuron layer to a feed forward process neural network and applying the normalized exponential activation function to the hidden layer. Classification equivalence between probabilistic process neural networks and Bayesian rules was analyzed and a concrete learning algorithm presented. Experimental results showed the effectiveness of the proposed model and algorithm.
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