Abstract
This letter presents a new memristor crossbar array system and demonstrates its applications in image learning. The controlled pulse and image overlay technique are introduced for the programming of memristor crossbars and promising a better performance for noise reduction. The time-slot technique is helpful for improving the processing speed of image. Simulink and numerical simulations have been employed to demonstrate the useful applications of the proposed circuit structure in image learning.
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Acknowledgments
This work was jointly supported by the Fundamental Research Funds for the Central Universities under Grant CDJXS12180010, this research is also jointly supported by the National Natural Science Foundation of China (Grant no. 61374048) and the National Priority Research Project NPRP 4-1162-1-181 funded by Qatar National Research Fund, Qatar. The authors wish to thank Dr. Shiping Wen for helpful discussions.
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Chen, L., Li, C., Huang, T. et al. Memristor crossbar-based unsupervised image learning. Neural Comput & Applic 25, 393–400 (2014). https://doi.org/10.1007/s00521-013-1501-0
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DOI: https://doi.org/10.1007/s00521-013-1501-0