一种基于阶梯阈值的射线违禁品探测方法

在γ射线违禁品探测技术中,快速准确的γ射线康普顿散射信号平滑具有非常重要的意义。现有的多项式平滑法和小波分析方法不仅运算速度慢,且易受噪声干扰,容易出现弱峰、谱峰错位等问题。为解决上述问题,提出一种新的基于阶梯阈值的散射信号分析方法。首先通过数据预处理,计算康普顿散射信号的基底变量,然后根据自适应阶梯阈值和测量差值,依次迭代更新背散射数据,进行信号滤波,最后自动检测峰位,实现可疑物识别。实验结果表明,相比现有的信号分析方法,阶梯阈值算法能够降低噪声干扰,保留康普顿散射信号的峰值和峰位,运算速度快,满足便携式探测设备的实时性要求。Fast and accurate Compton scattering signal smoothing plays an important part for γ-ray-based contraband identification.Traditional methods based on polynomial averaging or wavelet analysis are not only slow but also sensitive to noise,which makes them suffer from issues such as peak amplitude decrease and peak dislocation.A new method based on step threshold is proposed for scattering signal analysis,which can overcome aforementioned issues.Firstly,the base value for Compton scattering signal is computed via data pre-processing.Secondly,the scattering data is iteratively updated using adaptive threshold and system measurement,thus producing smoothed signal data.At last,the peak is localized from the filtered signal data and abnormality is identified.Experimental results show that our method is robust against noise compared to existing methods.The amplitude and location of the peak can be accurately perceived and identified.The method is efficient and can be deployed on portable contraband detection devices.     

高阶优化算法分析简介

高阶优化算法是利用目标函数的高阶导数信息进行优化的算法,是最优化领域中的一个新兴的研究方向.高阶算法具有更低的迭代复杂度,但是需要求解一个更难的子问题.主要介绍三种高阶算法,分别为求解凸问题的高阶加速张量算法和A-HPE框架下的最优张量算法,以及求解非凸问题的ARp算法.同时也介绍了怎样求解高阶算法的子问题.希望通过对高阶算法的介绍,引起更多学者的关注与重视.