Accelerating Deep Neural Networks with Analog Memory Devices
Katherine Spoon, Stefano Ambrogio, et al.
IMW 2020
We discuss thermal fixing as a solution to the volatility problem in holographic storage systems that use photorefractive materials such as LiNbO3. We present a systematic study to characterize the effect of thermal fixing on the error performance of a large–scale holographic memory. We introduce a novel, to our knowledge, incremental fixing schedule to improve the overall system fixing efficiency. We thermally fixed 10,000 holograms in a 90°–geometry setup by using this new schedule. All the fixed holograms were retrieved with no errors. © 1999 Optical Society of America.
Katherine Spoon, Stefano Ambrogio, et al.
IMW 2020
Geoffrey W. Burr
SPIE Optical Science and Technology 2003
Geoffrey W. Burr, Stefano Ambrogio, et al.
CSTIC 2019
Marí P. Bernal, Geoffrey W. Burr, et al.
Applied Optics