Hopfield Network based Control and Diagnostics System for Accelerators
Accelerator Physics
2018-08-07 v1
Abstract
A recurrent artificial neural network known as Hopfield network is used for pattern storage. Here we have applied this associative memory type network for pattern recognition for predictive controls and diagnostics in accelerator based systems. This system will be usefull for control systems and data acquisition system based on artificial intelligence at accelerator facilities. In this publication we have discussed the role of Hopfield network as pattern recognition and auto encoder for denoising the images of ion beams obtained using CCD based optical systems.
Keywords
Cite
@article{arxiv.1808.01936,
title = {Hopfield Network based Control and Diagnostics System for Accelerators},
author = {N. Joshi and O. Meusel and H. Podlech},
journal= {arXiv preprint arXiv:1808.01936},
year = {2018}
}