细胞神经网络方法在等离子体融合实时图像分析中的应用

G. Vagliasindi, A. Murari, P. Arena, L. Fortuna, G. Mazzitelli
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引用次数: 5

摘要

在现代托卡马克中,可见光和红外摄像机在监测核聚变实验过程中的等离子体演化方面变得越来越重要。实时分析这些图像可以为等离子体的控制和机器的安全提供相关信息。基于细胞非线性网络的芯片的实时图像处理能力已经应用于弗拉斯卡蒂托卡马克升级和欧洲联合环面等多个任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Cellular Neural Network Methods to Real Time Image Analysis in Plasma Fusion
In modern tokamaks visible and infrared video cameras are becoming more and more important to monitor plasma evolution during fusion experiments. Analyzing these images in real-time can provide relevant information for controlling the plasma and the safety of the machines. The realtime image processing capability of Cellular Nonlinear Network based chip has been applied to several tasks both at the Frascati Tokamak Upgrade and the Joint European Torus.
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