基于LSSVM的γ能谱平滑方法

γ能谱平滑的效果直接影响寻峰、解谱的精度,为此需要在消除放射性计数的统计涨落,提高信噪比的同时最大程度地保留能谱特征信息。本文采用基于结构风险化最小准则的最小二乘支持向量机方法 LSSVM,结合交叉验证参数寻优方法对Na I(Tl)γ能谱进行平滑处理,实验结果表明:LSSVM能谱平滑在全谱上保持较好峰形而不形变,各谱峰位置与理论计算值的最大误差(即峰偏)≤0.6个道址,平均误差为0.43个道址;且该方法具备良好的适应性和推广能力。

A Smooth Method ofγSpectrum Based on LSSVM

The accuracy of γspectrum smoothing has a direct effect on the accuracy of peak searching and spec -trum unscrambling .Therefore it needs to not only reduce and suppress the statistical fluctuation of radioactive counts and improve noise -signal ratio , but also persist the main character of the spectrum .This paper adopts the improved Support Vector Machine , LSSVM method which based on structural risk minimization criterion (SRM criterion) regression, and then combines with cross validation parameter optimization method , to smoot-hing NaI ( Tl) γspectrum.The experimental results show that the smooth result of the method based on LSSVM can keep peak form with no deformation , the maximum error of each spectral peak position is no more than 0 .5 channel, the average error value is 0.35 channel, besides, this method has good adaptability and generalization ability.