Hardware realization of a fast neural network algorithm for real-time tracking in HEP experiments
Hardware realization of a fast neural network algorithm for real-time tracking in HEP experiments
复制标题
HEP实验中实时跟踪的快速神经网络算法的硬件实现
DOI：
10.1016/0168-9002(95)00449-1
复制
发表时间：
1995
影响因子：
1.4
通讯作者：
H. Wendler
中科院分区：
文献类型：
--
作者：
F. Leimgruber;P. Pavlopoulos;M. Steinacher;L. Tauscher;S. Vlachos;H. Wendler
本文介绍了一种基于人工神经网络算法（ANN）的HEP实验快速模式识别系统。在不到75 ns的时间内确定事件中轨迹的多重性和位置。第一级触发器的硬件模块使用CPLEAR实验的数据进行了广泛的性能和可靠性测试。
A fast pattern recognition system for HEP experiments, based on artificial neural network algorithms (ANN), has been realized with standard electronics. The multiplicity and location of tracks in an event are determined in less than 75 ns. Hardware modules of this first level trigger were extensively tested for performance and reliability with data from the CPLEAR experiment.