基于小波分析的神经网络识别毒剂的研究
Study on the Neural Networks for Distinguishing Chemical Agents Base on the Wavelet Analysis
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摘要: 为快速、准确地识别毒剂,在分析神经网络识别毒剂基本方法的基础上,建立了带有偏差单元的递归神经网络识别毒剂模型,包括神经网络识别毒剂的学习算法和基于小波分析的毒剂特征提取.通过剖析神经网络识别毒剂模型,设计了神经网络识别毒剂的软件,实现了神经网络对毒剂的识别.用沙林模拟数据进行了测试和分析,结果表明,利用与化学传感器相联结的神经网络识别毒剂,是实现毒剂识别自动化、智能化的一种有效方法.Abstract: The basic method of the neural networks for distinguishing chemical agents were analyzed.For fastness and accuracy,the model of the neural networks distinguishing chemical agents was built by the returning neural networks with deviation unit,including its calculating method and the chemical agents feature extraction based on the wavelet analysis we have analysed the neural networks model for distinguishing chemical agents,put forward the strategy,designed the software,realized the neural networks for distinguishing chemical agents.After analyzing and discussing the results a conclusion is drawn that it is a kind of valid method to realize the automation and intelligence of distinguishing chemical agents using the neural networks combined with chemical sensor.
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