Improvement of algorithms for digital real-time n-γ discrimination

Three algorithms（the Charge Comparison Method,n-γ Model Analysis and the Centroid Algorithm）have been revised to improve their accuracy and broaden the scope of applications to real-time digital n-γ discrimination.To evaluate the feasibility of the revised algorithms,a comparison between the improved and original versions of each is presented.To select an optimal real-time discrimination algorithm from these six algorithms（improved and original）,the figure-of-merit（FOM）,Peak-Threshold Ratio（PTR）,Error Probability（EP） and Simulation Time（ST） for each were calculated to obtain a quantitatively comprehensive assessment of their performance.The results demonstrate that the improved algorithms have a higher accuracy,with an average improvement of 10%in FOM,95%in PTR and 25%in EP,but all the STs are increased.Finally,the Adjustable Centroid Algorithm（ACA） is selected as the optimal algorithm for real-time digital n-γ discrimination.