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Detection and clustering of light charged particles via system-identification techniques

机译:通过系统识别技术对带电粒子进行检测和聚类

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The problem considered in this work is the classification of the particles produced by the collision of a heavy ion beam on a target. Each particle is captured by a detector and results in a signal (which is the impulse response of a dynamic linear system), which is measured by a digital acquisition system. The assumption made herein is that the shape of the impulse-response contains complete information on the particle, and the classification can be done by pulse-shape, analysis.rnIn this work, a complete procedure for the particle identification is proposed. The main idea is to use the cascade of a state-space identification algorithm and a parametric non-linear map using the model parameters as input regressors. The algorithm has been tested on a large set of impulse-responses and provides a fully automatic accurate classification of the isotopes.rnThis work focuses on isotopic identification of the most energetic light charged particles (LCP). All the experiments are made with the large detector array CHIMERA (Charge Heavy Ions Mass and Energy Resolving Array).
机译:这项工作中考虑的问题是重离子束与目标碰撞产生的颗粒的分类。每个粒子被检测器捕获,并产生信号(这是动态线性系统的脉冲响应),该信号由数字采集系统测量。本文假设脉冲响应的形状包含有关粒子的完整信息,并且可以通过脉冲形状分析进行分类。在这项工作中,提出了用于粒子识别的完整程序。主要思想是使用状态空间识别算法和使用模型参数作为输入回归变量的参数化非线性映射的级联。该算法已在大量脉冲响应上进行了测试,并提供了同位素的全自动准确分类。这项工作着重于对高能带电粒子(LCP)的同位素识别。所有实验均使用大型探测器阵列CHIMERA(电荷重离子质量和能量分辨阵列)进行。

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