Variation-tolerant, low-power, and high endurance read scheme for memristor memories
Author:
Publisher
Springer Science and Business Media LLC
Subject
Surfaces, Coatings and Films,Hardware and Architecture,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s10470-020-01702-0.pdf
Reference46 articles.
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2. Bao, B., Hu, A., Bao, H., Xu, Q., Chen, M., & Wu, H. (2018). Three-dimensional memristive Hindmarsh–Rose neuron model with hidden coexisting asymmetric behaviors. Complexity 2018, 3872573.
3. Bao, B., Qian, H., Quan, X., Chen, M., Wang, J., & Yajuan, Yu. (2017). Coexisting behaviors of asymmetric attractors in hyperbolic-type memristor based hopfield neural network. Frontiers in Computational Neuroscience, 11, 81.
4. Berzina, T., Smerieri, A., Ruggeri, G., Erokhin, V., & Fontana, M. P. (2010). Role of the solid electrolyte composition on the performance of a polymeric memristor. Materials Science and Engineering C, 30(3), 407–411.
5. Chanthbouala, A., Garcia, V., Cherifi, R. O., Bouzehouane, K., Fusil, S., Moya, X., et al. (2012). A ferroelectric memristor. Nature Materials, 11(10), 860.
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