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Time of the last modification database: 2021-04-30 12:54:22
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  1. Li, L., Xu, R., Gan, Q., Lin, J., Synchronization of neural networks with memristor-resistor bridge synapses and Lévy noise. Neurocomputing, vol.432, pp.262-274, 7th April 2021.
  2. Ryu, J.-H., Kim, S., Kim, B., Hussain, F., Mahata, C., Ismail, M., Kim, Y., Bio-inspired synaptic functions from a transparent zinc-tin-oxide-based memristor for neuromorphic engineering. Applied Surface Science, vol.544, pp.1-9, 1st April 2021.
  3. Ahir, N.A., Takaloo, A.V., Nirmal, K.A., Kundale, S.S., Bae, J., Chougale, M.Y., Kim, D.-K., Dongale, T.D., Capacitive coupled non-zero I–V and type-II memristive properties of the NiFe2O4–TiO2 nanocomposite. Materials Science in Semiconductor Processing, pp.1-10, April 2021.
  4. Panda, D., Kumari, R., Pradhan, A., Modelling and Evolution of Conducting Filament in TiO x Memristor Using Conducting Atomic Force Microscopy. Journal of Nanoscience and Nanotechnology, vol.21, no.3, pp.1590-1597, 1st March 2021.
  5. Kim, S., Eshraghian, J.K., Lee, J., Eshraghian, K., Cho, K., Quantized Convolutional Neural Network Implementation on a Parallel-Connected Memristor Crossbar Array for Edge AI Platforms. Journal of Nanoscience and Nanotechnology, vol.21, no.3, pp.1854-1861, 1st March 2021.
  6. Kim, K., Eshraghian, K., Kang, H., Cho, K., Nano-Crossbar Weighted Memristor-Based Convolution Neural Network Architecture for High-Performance Artificial Intelligence Applications. Journal of Nanoscience and Nanotechnology, vol.21, no.3, pp.1833-1844, 1st March 2021.
  7. Desai, T.R., Dongale, T.D., Patil, S.R., Tiwari, A.P., Pawar , P.K., Kamat, R.K., Kim, T.G., Synaptic learning functionalities of inverse biomemristive device based on trypsin for artificial intelligence application. Journal of Materials Research and Technology, vol.11, pp.1100-1110, March 2021.
  8. Liu, Y., Wang, C., Li, Z., Wang, Y., Lu, W., Huang, H., Effects of W/WO3-x junction on synaptic characteristics of W/WO3-x/ITO memristor. Physica E: Low-dimensional Systems and Nanostructures, vol.127, pp.1-7, March 2021.
  9. Caldarola, F., Pantano, P., Bilotta, E., Computation of Supertrack Functions for Chua's Oscillator and for Chua's Circuit with Memristor. Communications in Nonlinear Science and Numerical Simulation, vol.94, pp.1-16, March 2021.
  10. Rao, X.-B., Zhao, X.-P., Gao, J.-S., Zhang, J.-G., Self-organizations with fast-slow time scale in a memristor-based Shinriki's circuit. Communications in Nonlinear Science and Numerical Simulation, vol.94, pp.1-19, March 2021.
  11. Pisarev, A., Busygin, A., Bobylev, A., Gubin, A., Udovichenko, S., Fabrication technology and electrophysical properties of a composite memristor-diode crossbar used as a basis for hardware implementation of a biomorphic neuroprocessor. Microelectronic Engineering, vol.236, pp.1-9, 15th February 2021.
  12. Biolek, D., Kolka, Z., Biolková, V., Kvatinsky, S., Biolek, Z., (V)TEAM for SPICE Simulation of Memristive Devices With Improved Numerical Performance. IEEE Access, vol.9, pp.30242-30255, 12th February 2021.
  13. Iswarya, M., Raja, R., Cao, J., Niezabitowski, M., Alzabut, J., Maharajan, C., New results on exponential input-to-state stability analysis of memristor based complex-valued inertial neural networks with proportional and distributed delays. Mathematics and Computers in Simulation, pp.1-22, 9th February 2021.
  14. Sirotkin, V.V., Tulina, N.A., Applying Numerical Simulation for the Investigation of Memristor Structures Based on Oxides and Chalcogenides. Russian Microelectronics, vol.49, pp.562-567, 8th February 2021.
  15. Matyushkin, I.V., Nonlinear Dynamic Approach in Analyzing the Instability of Memristor Parameters. Russian Microelectronics, vol.49, pp.554-561, 8th February 2021.
  16. Xu, S.-G., Zhang, P., Zhang, X., Design of memristor materials from ordered-vacancy zincblende semiconductors. Physical Review Materials, vol.5, pp.1-7, 8th February 2021.
  17. Caravelli, F., Sheldon, F.C., Traversa, F.L., Global minimization via classical tunneling assisted by collective force field formation. arXiv:2102.03385, [cond-mat.mes-hall], 5th February 2021.
  18. Zhu, B., Fan, Q., Wang, D., Chaos suppression for a Buck converter with the memristive load. Analog Integrated Circuits and Signal Processing, vol.107, pp.309-318, 2nd February 2021.
  19. Yu, S., Shafik, R., Bunnam, T., Chen, K., Yakovlev, A., Optimized Multi-Memristor Model based Low Energy and Resilient Current-Mode Multiplier Design. Design, Automation and Test in Europe Conference, pp.1-4, 1st February 2021.
  20. Gnoli, L., Riente, F., Ottavi, M., Vacca, M., A memristor-based sensing and repair system for photovoltaic modules. Microelectronics Reliability, vol.117, pp.1-9, February 2021.
  21. Sharma, V.K., Parveen, T., Ansari, M.S., Four Quadrant Analog multiplier based Memristor Emulator using Single Active Element. AEU - International Journal of Electronics and Communications, vol.130, pp.1-18, February 2021.
  22. Alonso, F.J., Maldonado, D., Aguilera, A.M., Roldan, J.B., Memristor variability and stochastic physical properties modeling from a multivariate time series approach. Chaos, Solitons & Fractals, vol.143, pp.1-7, February 2021.
  23. Morozov, A.Y., Abgaryan, K.K., Reviznikov, D.L., Mathematical model of a neuromorphic network based on memristive elements. Chaos, Solitons & Fractals, vol.143, pp.1-10, February 2021.
  24. Sun, J., Han, J., Liu, P., Wang, Y., Memristor-Based Neural Network Circuit of Pavlov Associative Memory with Dual Mode Switching. AEU - International Journal of Electronics and Communications, vol.129, pp.1-9, February 2021.
  25. Peng, Y., He, S., Sun, K., A higher dimensional chaotic map with discrete memristor. AEU - International Journal of Electronics and Communications, vol.129, pp.1-7, February 2021.
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