面向缪子成像求解的抗噪增强牛顿算法  

An enhanced noise-resistant Newton algorithm for solving muon imaging problems

作　　者：刘梅 任永杰 李婷 LIU Mei;REN Yong-jie;LI Ting(School of Information Science and Engineering,Lanzhou University,Lanzhou 730000,China;College of Computer,Qinghai Normal University,Xining 810008,China)

机构地区：[1]兰州大学信息科学与工程学院,兰州730000 [2]青海师范大学计算机学院,西宁810008

出　　处：《兰州大学学报(自然科学版)》2025年第1期1-7,16,共8页Journal of Lanzhou University(Natural Sciences)

基　　金：国家自然科学基金青年科学基金项目(62306130)。

摘　　要：在缪子成像时的数据采集过程中,受到环境噪声、仪器噪声和统计噪声的影响,可能会干扰成像结果的准确性,需在成像过程中对噪声进行抑制,以提高成像结果的准确性和可靠性.若已知解空间的上、下限,将其作为约束条件引入缪子成像的过程中,以避免成像结果超出预期范围,从而更有效地得到缪子成像问题的解.提出一种带有双端约束的抗噪增强牛顿算法,理论分析证明其在有噪声条件下具有较小的稳态误差.与现有算法的仿真结果对比表明,本研究算法在求解缪子成像问题时的还原准确度较高,在重要指标上的表现较好.The process of data acquisition of muon imaging is usually affected by environmental noise,instrument noise,and statistical noise that may interfere with the accuracy of imaging results,so it is necessary to suppress noise in the imaging process to improve the accuracy and reliability of imaging results.If the upper and lower limits of the solution space are known in advance,the information thereof can be introduced into the process of muon imaging as a constraint condition so that the imaging results can be protected from exceeding the expected range,and the solution of muon imaging problem can be obtained more effectively.An enhanced noise-resistant Newton algorithm with double bound limits is proposed,and theoretical analyses verify that the proposed algorithm had a small steady-state error under noise.Compared with existing algorithms,the simulation results indicate that the algorithm proposed achieves higher reconstruction accuracy in solving the muon imaging problem and performs better on key metrics.

关 键 词：缪子成像 双端约束 抗噪 增强牛顿算法 

分 类 号：TP3-05[自动化与计算机技术—计算机科学与技术]