|
|
|
Список литературы
|
|
|
1. |
Zhang J, Pégard N, Zhong J, Adesnik H, Waller L, “3D computer-generated holography by non-convex optimization”, Optica, 4:10 (2017), 1306–1313 |
2. |
Wang H, Piestun R, “Dynamic 2D implementation of 3D diffractive optics”, Optica, 5:10 (2018), 1220–1228 |
3. |
Lin X, Rivenson Y, Yardimci NT, Veli M, Luo Y, Jarrahiand M, Ozcan A, “All-optical machine learning using diffractive deep neural networks”, Science, 361:6406 (2018), 1004–1008 |
4. |
Schmidt S, Thiele S, Toulouse A, Bösel C, Tiess T, Herkommer A, Gross H, Giessen H, “Tailored micro-optical freeform holograms for integrated complex beam shaping”, Optica, 7:10 (2020), 1279–1286 |
5. |
Zhou T, Fang L, Yan T, Wu J, Li Y, Fan J, Wu H, Lin X, Dai Q, “In situ optical backpropagation training of diffractive optical neural networks”, Photon Res, 8:6 (2020), 940–953 |
6. |
Gerchberg R, Saxton W, “A practical algorithm for the determination of phase from image and diffraction plane pictures”, Optik, 35 (1972), 237 |
7. |
Fienup JR, “Phase retrieval algorithms: a comparison”, Appl Opt, 21:15 (1982), 2758–2769 |
8. |
Soifer VA, Kotlyar VV, Doskolovich LL, Iterative methods for diffractive optical elements computation, Taylor & Francis Ltd, London:, 1997 |
9. |
Shechtman Y, Eldar YC, Cohen O, Chapman HN, Miao JW, Segev M, “Phase retrieval with application to optical imaging”, IEEE Signal Process Mag, 32:3 (2015), 87–109 |
10. |
Latychevskaia T, “Iterative phase retrieval in coherent diffractive imaging: practical issues”, Appl Opt, 57:25 (2018), 7187–7197 |
11. |
Ripoll O, Kettunen V, Herzig HP, “Review of iterative Fourier transform algorithms for beam shaping applications”, Opt Eng, 43:11 (2004), 2549–2556 |
12. |
Doskolovich LL, Mingazov AA, Byzov EV, Skidanov RV, Ganchevskaya SV, Bykov DA, Bezus EA, Podlipnov VV, Porfirev AP, Kazanskiy NL, “Hybrid design of diffractive optical elements for optical beam shaping”, Opt Express, 29:20 (2021), 31875-31890 |
13. |
Gülses AA, Jenkins BK, “Cascaded diffractive optical elements for improved multiplane image reconstruction”, Appl Opt, 52:15 (2013), 3608–3616 |
14. |
Deng X, Chen RT, “Design of cascaded diffractive phase elements for three-dimensional multiwavelength optical interconnects”, Opt Lett, 25:14 (2000), 1046–1048 |
15. |
Yan T, Wu J, Zhou T, Xie H, Xu F, Fan Jo, Fang L, Lin X, Dai Q, “Fourier-space diffractive deep neural network”, Phys Rev Lett, 123:2 (2019), 023901 |
16. |
Zheng S, Xu S, Fan D, “Orthogonality of diffractive deep neural network”, Opt Lett, 47:7 (2022), 1798–1801 |
17. |
Chang J, Sitzmann V, Dun X, Heidrich W, Wetzstein G, “Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification”, Sci Rep, 8 (2018), 12324 |
18. |
Liu C, Ma Q, Luo ZJ, Hong QR, Xiao Q, Zhang HC, Miao L, Yu WM, Cheng Q, Li L, Cui TJ, “A programmable diffractive deep neural network based on a digital-coding metasurface array”, Nat Electron, 5 (2022), 113–122 |
19. |
Mengu D, Luo Y, Rivenson Y, Ozcan A, “Analysis of diffractive optical neural networks and their integration with electronic neural networks”, IEEE J Sel Top Quantum Electron, 26:1 (2020), 3700114 |
20. |
Sui X, Wu Q, Liu J, Chen Q, Gu G, “A review of optical neural networks”, IEEE Access, 8 (2020), 70773–70783 |
21. |
Chen H, Feng J, Jiang M, Wang Y, Lin J, Tan J, Jin P, “Diffractive deep neural networks at visible wavelengths”, Engineering, 7:10 (2021), 1483–1491 |
22. |
Kulce O, Mengu D, Rivenson Y, Ozcan A, “All-optical synthesis of an arbitrary linear transformation using diffractive surfaces”, Light Sci Appl, 10 (2021), 196 |
23. |
Luo Y, Mengu D, Yardimci NT, Rivenson Y, Veli M, Jarrahiand M, Ozcan A, “Design of task-specific optical systems using broadband diffractive neural networks”, Light Sci Appl, 8 (2019), 112 |
24. |
Kingma DP, Ba J, Adam: A method for stochastic optimization, 2015, arXiv: 1412.6980 |
25. |
Lecun Y, Bottou L, Bengio Y, Haffner P, “Gradient-based learning applied to document recognition”, Proc IEEE, 86:11 (1998), 2278–2324 |