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《Journal of China University of Metrology》 2013-01
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The γ spectrum analysis based on optimal linear associative memory networks

Qian Jin1,Wang Hongyan2,Shi Hongsheng1,Shu Kangying1(1.College of Materials Science and Engineering,China Jiliang University,Hangzhou 310018,China; 2.China Institute of Atomic Energy,Beijing 102413,China)  
A qualitative identification and a quantitative analysis of the γ spectrum based on the use of optimal linear associative memory neural network were studied.Compared with the traditional unfolding methods,the OLAM network possesses the properties of low operating demands,high speed and accurate identification of double complex γ spectrum.The full spectrum input method which made use of the information of the entire energy spectrum reduced the requirements of energy resolution of the detector and avoided peak searching,energy calibration and efficiency calibration.This method provides a basis for the development of spectrum solution software of high-performance portable detectors and can be an effective means of spectrum analysis.
【CateGory Index】: TP183
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