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Time of the last modification database: 2017-02-20 10:07:30
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  1. Zhang, L., Yang, Y., Wang, F., Projective synchronization of fractional-order memristive neural networks with switching jumps mismatch. Physica A: Statistical Mechanics and its Applications, vol.471, pp.402–415, 1st April 2017.
  2. Liu, S., Ren, A., Varshney, P.K., Wang, Y., Ultra-Fast Robust Compressive Sensing Based on Memristor Crossbars. ICASSP 2017, pp.1-10, 5th March 2017.
  3. Babacan, Y., Kaçar, F., Memristor emulator with spike-timing-dependent-plasticity. AEU - International Journal of Electronics and Communications, vol.73, pp.16–22, March 2017.
  4. Wang, Ch., Xia, H., Zhou, L., Implementation of a new memristor-based multiscroll hyperchaotic system. Pramana, vol.88, no.34, pp.1-7, 17th February 2017.
  5. Kanygin, M.A., Katkov, M.V., Pershin, Y.V., Similarity between the response of memristive and memcapacitive circuits subjected to ramped voltage. Journal of Nanophotonics, vol.11, no.3,, 10th February 2017.
  6. Murdoch, B.J., McCulloch, D.G., Partridge, J.G., Synaptic plasticity and oscillation at zinc tin oxide/silver oxide interfaces. Journal of Applied Physics, vol.121, no.5, pp.1-6, 7th February 2017.
  7. Dias, C., Lv, H., Picos, R., Aguiar, P., Cardoso, S., Freitas, P.P., Ventura, J., Bipolar Resistive Switching in SiAg Nanostructures. Applied Surface Science, pp.1-12, 4th February 2017.
  8. Maier, P., Hartmann, F., Emmerling, M., Schneider, C., Kamp, M., Worschech, L., Höfling, S., Associative learning with Y-shaped floating gate transistors operated in memristive modes. Applied Physics Letters, vol.110, no.5, pp.1-4, 3rd February 2017.
  9. Tu, Z., Cao, J., Alsaedi, A., Alsaadi, F., Global dissipativity of memristor-based neutral type inertial neural networks. Neural Networks, vol.00 (2016), pp.1-13, 3rd February 2017.
  10. Zhang, X.Y., Shao, J., Chen, Y., Chen, W., Yu, J., Wang, B., Zheng, Y., The dynamic conductance response and mechanics-modulated memrisitive behavior of Azurin monolayer under cyclic loads. Physical Chemistry Chemical Physics, pp.1-30, 1st February 2017.
  11. Lee, M.J., The study of Two-dimensional van der Waals material memristor device. NanoPortugal International Conference, pp.1, 1st February 2017.
  12. Suri, M., Merkel, C., Kudithipudi, D., Wysocki, B., Stochastic CBRAM-Based Neuromorphic Time Series Prediction System. ACM Journal on Emerging Technologies in Computing Systems (JETC), vol.13, no.3, article no.37, pp.1-14, February 2017.
  13. Ranjan, R.K., Rani, N., Pal, R., Paul, S.K., Kanyal, G., Single CCTA based high frequency floating and grounded type of incremental/decremental memristor emulator and its application. Microelectronics Journal, vol.60, pp.119–128, February 2017.
  14. Liu, J., Xu., R., Passivity analysis and state estimation for a class of memristor-based neural networks with multiple proportional delays. Advances in Difference Equations, vol.2017, no.1, article no.34, pp.1-20, 31st January 2017.
  15. Faruque, K. A., Biswas, B. R., Rashid, A. B. M. H., Memristor-Based Low-Power High-Speed Nonvolatile Hybrid Memory Array Design. Circuits, Systems, and Signal Processing, pp.1-13, 30th January 2017.
  16. Lu, Y., Liang, Q., Huang, X., Parameters self-tuning PID controller circuit with memristors. International Journal of Circuit Theory and Applications, vol. 45, no.1, pp.17, 25th January 2017.
  17. Biolek, Z., Biolek, D., Biolková, V., Kolka, Z., Ascoli, A., Tetzlaff, R., Analysis of memristors with nonlinear memristance versus state maps. International Journal of Circuit Theory and Applications, vol.45, no.1, pp.19, 25th January 2017.
  18. Merkel, C., Kudithipudi, D., Neuromemristive Systems: A Circuit Design Perspective. Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices, vol.31, Cognitive Systems Monographs, pp.45-64, 24th January 2017.
  19. Kim, Y.-S., Shin, S.-H., Secco, J., Min, K.-S., Corinto, F., Memristor-Based Platforms: A Comparison Between Continous-Time and Discrete-Time Cellular Neural Networks. Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices, vol.31, Cognitive Systems Monographs, pp.65-79, 24th January 2017.
  20. La Barbera, S., Alibart, F., Synaptic Plasticity with Memristive Nanodevices. Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices, vol.31, Cognitive Systems Monographs, pp.17-43, 24th January 2017.
  21. Li, R., Cao, J., Fixed-time synchronization of delayed memristor-based recurrent neural networks. SCIENCE CHINA Information Sciences, vol.60, pp.1-15, 23rd January 2017.
  22. Wang, L.-G., Zhang, W., Chen, Y., Cao, Y.-Q., Li, A.-D., Wu, D., Synaptic Plasticity and Learning Behaviors Mimicked in Single Inorganic Synapses of Pt/HfOx/ZnOx/TiN Memristive System. Nanoscale Research Letters, vol.12, no.65, pp.1-8, 23rd January 2017.
  23. Xu, B.-R., Wang, G.-Y., Meminductive Wein-bridge chaotic oscillator. Acta Physica Sinica, vol.66, no.2, pp.1-13, 20th January 2017.
  24. Braund, E., Miranda, E.R., Interactive Musical Biocomputer: an Unconventional Approach to Research in Unconventional Computing. Symmetry: Culture & Science, vol.28, no.1, pp.7-20, 20th January 2017.
  25. Solan, E., Dirkmann, S., Hansen, M., Schroeder, D., Kohlstedt, H., Ziegler, M., Mussenbrock, T., Ochs, K., An Enhanced Lumped Element Electrical Model of a Double Barrier Memristive Device. arXiv:1701.08068, [cs.ET], 19th January 2017.
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