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3 October 2022 Data reconstruction based on deep learning in holographic data storage
Xiao Lin, Jianying Hao, Yongkun Lin, Hongjie Liu, Ruixian Chen, Xiaodi Tan
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Proceedings Volume 12231, ODS 2022: Industrial Optical Devices and Systems; 122310G (2022) https://doi.org/10.1117/12.2635173
Event: SPIE Optical Engineering + Applications, 2022, San Diego, California, United States
Abstract
Holographic data storage is one powerful potential technology to solve the problem of mass data long-term storage. Deep learning is showing its advantages in many fields such as artificial intelligence, detection and imaging. When deep learning meets holographic data storage, new modulation ways and decoding methods were born. We did three kinds of modulation amplitude only, phase only and complex amplitude respectively in holographic data storage and used deep learning method to do data reconstruction. The results were better than previous reconstruction methods. Data reconstruction based on deep learning owns more anti-noise performance.
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Xiao Lin, Jianying Hao, Yongkun Lin, Hongjie Liu, Ruixian Chen, and Xiaodi Tan "Data reconstruction based on deep learning in holographic data storage", Proc. SPIE 12231, ODS 2022: Industrial Optical Devices and Systems, 122310G (3 October 2022); https://doi.org/10.1117/12.2635173
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KEYWORDS
Data storage
Holographic data storage systems
Holography
Modulation
Artificial intelligence
Phase shift keying
Tolerancing
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