Research on the Distinguishing Chemical Agents Based on the Neural Networks
Minghu Zhang, Dehu Wang, Shijun Lv, Huichuan Wang, Liu Hong, Youfeng Li · 2009
The basic method of the neural networks for distinguishing chemical agents was analyzed. For fastness and accuracy, connecting the wavelet analysis with the neural networks organically, and based on the wavelet transfer and the neural networks, the system of the speedy features extraction and identification for chemical agent, the Neural Networks Distinguishing Chemical Agent (NNDCA) system, is founded. The model of the NNDCA by the returning neural networks with deviation unit and the method of the feature extraction for the chemical agents based on the wavelet analysis are established, the realization idea of the NNDCA system is put forward, and the software structure of the NNDCA system is discussed. Based on experiments, the experimental and simulated results show: it is feasible that the analyses for the chemical agent with the NNDCA system. The method can remarkably heighten the accuracy and credibility of the measurement results, and the results are of repeatability.