Based on the double bound limits of the density of the measured object and the influence of noise on the measurement data,a computational neural dynamics algorithm for muon imaging was pro-posed,which can ensure that the results are within the constraint range.A theoretical analysis showed that,under the condition of no noise or constant noise,the algorithm converged globally to the theoretical solution of muon radiography,and could effectively suppress random noise.The simulation and compari-son results showed that the algorithm was effective and superior in solving the inversion problem.
computational neural dynamics algorithmcosmic ray muon radiographydouble bound lim-itinversion
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