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题名 基于γ特征谱的对象相似性识别技术研究
姓名 任忠国
院系 核科学与技术学院
专业 粒子物理与原子核物理
学位名称 理学博士
外文题名 Study of γ Spectra Characteristic Recognition Technology Based on Similarity
第一导师姓名 胡碧涛
关键词 γ能谱分析;γ能谱配准;模式识别; 相似性度量
外文关键词 γSpectra Analysis;γSpectra Registration;Pattern Recognition;Similarity
学科 理学
摘要 本论文围绕基于高分辨γ能谱的对象相似性识别技术,结合近十多年来高速发展的模式识别技术与图像配准技术,展开γ能谱对象的分类识别研究,为提升核保障技术水平,核军控、核裁军核查提供技术储备,以及下一步研究工作提供支持。本论文的研究基于VC++2010,通过与ROOT相结合,开发了相应的程序,完成的主要工作与获得的研究成果如下:1)采用传统的γ能谱分析方法对高分辨γ能谱进行了分析。主要分析工作包括:能谱平滑降噪、能谱寻峰、连续本底扣除、峰面积拟合等。寻峰算法为对称零面积法与反卷积法,本底扣除利用了SNIP法进行,峰面积拟合采用了AWMI方法。首次将小波降噪与多项式最小二乘平滑结合,对能谱进行平滑降噪,提升了平滑降噪效果。 2)针对γ能谱的修正,参照图像配准技术提出了γ能谱配准概念,首次展开了γ能谱配准研究。γ能谱基于特征的配准研究开展了γ能谱预处理、特征提取、特征匹配、插值重采样以及相似性度量等研究。重点研究了线性插值、拉格朗日插值、埃尔米特插值和三次样条插值等四种插值重构算法的γ能谱插值效果,结果表明埃尔米特插值效果优于其他插值算法。对于相似性度量研究,研究了χ2/(N-1)、拟合优度、欧氏距离、余弦相似度、皮尔逊积矩相关系数等算法。3)研究了模式识别中主成分分析、线性判别分析与支持向量机对γ能谱的分类识别。其中,国内首次开展了支持向量机研究与线性判别分析应用于γ能谱分析。
外文摘要 This paper centers on the object characteristic Recognition technology based on Similarity of high resolution γ spectra and combines the pattern recognition technology and image registration technology which have witnessed rapid development in the past ten years. It researches on the classified recognition of γ spectra objects, aiming to enhance nuclear safeguard technology, to provide technical reserve for nuclear arms control and nuclear disarmament and to offer support for further research work. Researches in the paper are made on the basis of VC++2010 and related programs have been developed in the process in combination with ROOT. Major works and research results accomplished are as follows: 1) Analyzing the high resolution γ spectra with traditional γ spectra analysis methods. Main analysis works include spectral smoothing and denoising, spectral peak searching, background continuum deduction, peak area fitting, etc. Peak-searching algorithm refers to symmetrical zero area method and deconvolution method, background continuum deduction is conducted by SNIP and peak area fitting is realized with the method of AWMI. For the first time, the research combines wavelet denoising and polynomial least squares smoothing to realize smoothing and denoising for the spectra and the smoothing and denoising degree is enhanced.2) Putting forward the concept of γ spectra registration specific to their correction with a reference to image registration technology and initiating the research on γ spectra registration. The research on character-based γ spectra registration covers γspectra preprocessing, character extraction, character matching, interpolation resampling, similarity measurement, etc. The paper focuses on researching the effects of γ spectra interpolation of four interpolation reconstruction algorithms, including Linear Interpolation, Lagrange Interpolation, Hermite Interpolation and Cubic Spline Interpolation, and results show that the effects of Hermite Interpolation is better than that of others. The similarity measurement is researched with algorithms such as χ2/ (N-1), Goodness of Fit, Euclidean Distance, Cosine Similarity, Pearson Product-moment Correlation Coefficient, etc. After interpolation resampling, the similarity measurement is researched following the multilevel registration after wavelet transform.3) Researching the classified recognition of γ spectra by Principal Component Analysis, Linear Discriminant Analysis and Support Ve...
研究领域 射线与物质相互作用及应用
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