摘要
研究了在北京正负电子对撞机 (BEPC)的BES谱仪实验中利用迭代判断分析法 (IDA)和神经元网络法 (NN)进行e,μ ,π粒子的鉴别。在完全相同的条件下给出了两种方法在 0 .2GeV/c到1.6GeV/c动量区间对 3类粒子的鉴别效率与本底水平。虽然用于训练的样本本身具有非均匀的动量谱 ,但两种方法的检验结果给出的粒子选择效率在整个动量区间仍然具有相当均匀的分布。结果表明 ,在这一应用中NN法要好于IDA法。对这两种方法各自的特色和适用条件进行了讨论。
The application of Iterative Discriminant Analysis (IDA) and Neural Networks (NN) methods for e, μ, π particle identification in BES experiment on BEPC collider was discussed. Under exactly the same condition, satisfactory identification efficiencies and background levels were given by both methods for those particles with momentum in the range from 0.2GeV to 1.6GeV. Although the momentum spectrum of the data samples used for training were non-uniform, it was interesting that the selection efficiencies given by test results from both method were quite uniform in the whole momentum range. It shows that the NN method is slightly better than IDA method. Their characteristics and application condition were also discussed.
出处
《核技术》
CAS
CSCD
北大核心
2001年第10期822-827,共6页
Nuclear Techniques
基金
国家自然科学基金资助项目 (19975 0 44 19991480 )
