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提出了以自适应网络模糊推理系统参数为识别特征的γ能谱指纹模糊识别方法.通过建模和仿真,提取了γ能谱指纹的模糊系统特征参数,并建立了关于系统特征参数的模糊集及模糊识别原则,以较高的置信度实现了γ能谱指纹的类型识别和个体识别.对实测γ能谱指纹进行了识别,对方法的识别性能进行了研究和探讨.研究表明,该方法不但具有较强的类型识别能力和个体识别能力,并具有较低的识别下限和较强的抗噪声能力.
A fuzzy identification method based on adaptive network fuzzy inference system parameters is proposed to identify γ energy fingerprint.After modeling and simulation, the fuzzy system feature parameters of γ energy spectrum fingerprinting are extracted and the fuzzy sets of system feature parameters are established And the principle of fuzzy identification, the type identification and individual identification of γ-energy fingerprinting were realized with high confidence.The real-time γ-energy fingerprints were identified and the recognition performance of the method was studied and discussed.The results show that this method Not only has a strong type recognition ability and individual recognition ability, and has a lower recognition limit and strong anti-noise ability.