@article{oai:kyutech.repo.nii.ac.jp:02000826,
 author = {高林, 正典 and Takabayashi, Masanori and 冨岡, 莉生 and Tomioka, Rio},
 issue = {3},
 journal = {フォトニクスニュース},
 month = {},
 note = {Self-referential holography (SRH) is a purely one-beam holographic data recording geometry based on a volume hologram recorded by self-interference of a spatially phase-modulated light. We have proposed to apply the principle of SRH for a holographic data storage without use of a reference beam, which is named self-referential holographic data storage (SR-HDS). Also, recently, we have found that SRH can be used as a deep neural network hardware by combining it with electronic calculations. In this paper, we mainly introduce the self-referential holographic deep neural network (SR-HDNN) and show proof-of-principle simulation results of 4-class image recognition task.},
 pages = {147--151},
 title = {自己参照型ホログラフィの原理を用いた光電子深層ニューラルネットワークハードウェア},
 volume = {9},
 year = {2024}
}