Feature Analysis and Recognition of Induced Uranium Components Fission Signal Based on BP Neural Network
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Graphical Abstract
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Abstract
The paper presents feature parameter analysis and processing in fission timedependent signal of induced uranium components based on BPNeural Networks through the analysis of the measuring principle and signal characteristics of induced uranium components fission signal. The auto correlation functions and cross correlation functions are calculated by using unbiased estimate， and then the feature parameters of fission signal in different status are extracted by using feature abstraction method， comparative method and derivative method， and then applied to training and prediction by means of BPneural networks based on pattern recognition. Theoretical analysis and the results show that， it is effective to obtain feature parameters of induced uranium component fission signal via comparative method and derivative method. UsingBP neural network to recognize patter of fission signal， we got good results that verified the effectiveness and reasonability of the method.
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