模糊识别理论在光谱数据中的应用

Fuzzy Recognition Theory in the Spectral Data

基于模糊模式识别理论,探析模糊模式识别方法在血液光谱数据识别中的应用,实现了对动物血液荧光光谱的特征提取与分类识别。在实验中,本文依据待处理样品光谱本身具有的模糊特性,运用模糊模式识别方法对光谱数据进行处理,并结合Matlab程序设计了分类效果较好的模糊分类器。实验结果表明,模糊识别方法在光谱数据中具有较强的识别能力,在光谱数据中具有较好的检测前景。

Based on the theories of fuzzy pattern recognition, this paper analyzes the application of the fuzzy pattern recognition method in blood spectrum data identification, achieves the extraction and classification of animal blood characteristic fluorescence spectrum. In this trial, we use fuzzy pattern recognition method to deal with sample spectrum on the basis of the fuzzy characteristics of the sample spectrum itself, and design fuzzy classifiers combined with Matlab programming which can reach an ideal classification effect. The results show that the fuzzy recognition method has a higher identification ability to the spectral data and good prospects in the detection of spectral data.