Research progress in optical neural networks: theory, applications and developments

被引:113
作者
Liu, Jia [1 ]
Wu, Qiuhao [1 ]
Sui, Xiubao [1 ]
Chen, Qian [1 ]
Gu, Guohua [1 ]
Wang, Liping [1 ]
Li, Shengcai [2 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Nanjing 210094, Peoples R China
[2] Army Res Inst, Inst Armored Forces, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Optical neural network; Deep learning; Optical linear operation; Optical nonlinearity; Training method; SCATTERING; LIGHT; DIFFRACTION; IMPLEMENTATION; SIMULATION; CORNERS; DESIGN; LAYERS; TIME; KERR;
D O I
10.1186/s43074-021-00026-0
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
With the advent of the era of big data, artificial intelligence has attracted continuous attention from all walks of life, and has been widely used in medical image analysis, molecular and material science, language recognition and other fields. As the basis of artificial intelligence, the research results of neural network are remarkable. However, due to the inherent defect that electrical signal is easily interfered and the processing speed is proportional to the energy loss, researchers have turned their attention to light, trying to build neural networks in the field of optics, making full use of the parallel processing ability of light to solve the problems of electronic neural networks. After continuous research and development, optical neural network has become the forefront of the world. Here, we mainly introduce the development of this field, summarize and compare some classical researches and algorithm theories, and look forward to the future of optical neural network.
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收藏
页数:39
相关论文
共 93 条
[1]   Numerical solution of the two-dimensional Helmholtz equation with variable coefficients by the radial integration boundary integral and integro-differential equation methods [J].
Al-Jawary, M. A. ;
Wrobel, L. C. .
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2012, 89 (11) :1463-1487
[2]  
Amin R, 2018, CONF LASER ELECTR
[3]  
Amin R, 2018, CONF LASER ELECTR
[4]   Speckle-learning-based object recognition through scattering media [J].
Ando, Takamasa ;
Horisaki, Ryoichi ;
Tanida, Jun .
OPTICS EXPRESS, 2015, 23 (26) :33902-33910
[5]   Soft porous silicone rubbers with ultra-low sound speeds in acoustic metamaterials [J].
Ba, Abdoulaye ;
Kovalenko, Artem ;
Aristegui, Christophe ;
Mondain-Monval, Olivier ;
Brunet, Thomas .
SCIENTIFIC REPORTS, 2017, 7
[6]   A hybrid training algorithm for feedforward neural networks [J].
Ben Nasr, Mounir ;
Chtourou, Mohamed .
NEURAL PROCESSING LETTERS, 2006, 24 (02) :107-117
[7]   Scattering Optics resolve Nanostructure [J].
Bertolotti, J. ;
van Putten, E. G. ;
Akbulut, D. ;
Vos, W. L. ;
Lagendijk, A. ;
Mosk, A. P. .
NANOENGINEERING: FABRICATION, PROPERTIES, OPTICS, AND DEVICES VIII, 2011, 8102
[8]   CONVOLUTION THEOREM IN MODERN ANALYSIS [J].
BLACKWELL, CA .
IEEE TRANSACTIONS ON EDUCATION, 1966, 9 (01) :29-32
[9]   NONLINEAR OPTICAL EFFECTS [J].
BRAUNSTEIN, R .
PHYSICAL REVIEW, 1962, 125 (02) :475-&
[10]   The interference of light and the quantum theory [J].
Breit, G .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1923, 9 :238-243