Application and Design of the Spectral Identification System Based on Neural Network and Fuzzy Control

Min Chen, Hui Liu
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Abstract

The spectral identification technology is a spectral basis of qualitative analysis. With the development of pattern recognition, spectral identification technology has become an important tool for rapid detection of medicine, environmental protection, petrochemical and other industries. The neural network nonlinear mapping, adaptive learning, robustness and fault tolerance features, has a wide range of applications in signal processing, knowledge engineering, pattern recognition and other fields. This paper meets the Lambert Beer law of spectral signals for the study, outlines the basic principles of neural networks for pattern recognition, and then according to the specific requirements of the spectrum recognition, multi-feature-based and neural network spectral identification programs, and conducts system design, the establishment of the basic model framework. Finally, an instance of the method is described.
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基于神经网络和模糊控制的光谱识别系统的应用与设计
光谱识别技术是定性分析的光谱基础。随着模式识别技术的发展,光谱识别技术已成为医药、环保、石化等行业快速检测的重要工具。神经网络具有非线性映射、自适应学习、鲁棒性和容错等特点,在信号处理、知识工程、模式识别等领域有着广泛的应用。本文以符合Lambert Beer定律的频谱信号为研究对象,概述了神经网络进行模式识别的基本原理,然后根据频谱识别的具体要求,提出了基于多特征和神经网络的频谱识别方案,并进行了系统设计,建立了基本的模型框架。最后,给出了该方法的一个实例。
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