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Time of the last modification database: 2016-12-05 10:21:55
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  1. 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.
  2. 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.
  3. Sahoo, S., Prabaharan, S.R.S., Nano-Ionic Solid State Resistive Memories (Re-RAM): A Review. Journal of Nanoscience and Nanotechnology, vol.17, no.1, pp.72-86, 1st January 2017.
  4. Khalid, M., Singh, J., Memristive Crossbar Circuits-Based Combinational Logic Classification Using Single Layer Perceptron Learning Rule. Journal of Nanoelectronics and Optoelectronics, vol.12, no.1, pp.47-58, January 2017.
  5. Cho, S.-W., Eshraghian, J., Eom, J.-S., Kim, S., Cho, K., Storage Logic Primitives Based on Stacked Memristor-CMOS Technology. Journal of Nanoscience and Nanotechnology, vol.16, no.12, pp.12726-12731, 1st December 2016.
  6. Adam, G.C., Hoskins, B.D., Prezioso, M., Strukov, D.B., Optimized stateful material implication logic for three-dimensional data manipulation. Nano Research, vol.9, no.12, pp.3914–3923, December 2016.
  7. Chen, H., Global Dynamics of Memristor Oscillator. International Journal of Bifurcation and Chaos, vol.26, no.12, December 2016.
  8. Abolmasoumi, A.H., Khosravinejad, S., Chaos Control in Memristor-Based Oscillators Using Intelligent Terminal Sliding Mode Controller. International Journal of Computer Theory and Engineering, vol.8, no.6, pp.506-511, December 2016.
  9. Babacan, Y., Kaçar, F., Floating memristor emulator with subthreshold region. Analog Integrated Circuits and Signal Processing, pp.1-5, 25th November 2016.
  10. Pershin, Y.V., Shevchenko, S.N., Computing with volatile memristors: An application of non-pinched hysteresis. arXiv:1611.08242v1, [cond-mat.mes-hall], 24th November 2016.
  11. Gul, F., Efeoglu, H., Bipolar resistive switching and conduction mechanism of an Al/ZnO/Al-based memristor. Superlattices and Microstructures, In Press, Accepted Manuscript, 23rd November 2016.
  12. Nili, H., Adam, G.C., Prezioso, M., Kim, J., Merrikh-Bayat, F., Kavehei, O., Strukov, D.B., Highly-Secure Physically Unclonable Cryptographic Primitives Using Nonlinear Conductance and Analog State Tuning in Memristive Crossbar Arrays. arXiv:1611.07946v1, [cs.ET], 23rd November 2016.
  13. Yan, L., Zhang, S., Ding, D., Liu, Y., Alsaadi, F.E., H∞ State Estimation for Memristive Neural Networks with Multiple Fading Measurements. Neurocomputing, In Press, Accepted Manuscript, 23rd November 2016.
  14. Wang, G., Jiang, S., Wang, X., Shen, Y., Yuan, F., A Novel Memcapacitor Model and Its Application for Generating Chaos. Mathematical Problems in Engineering, pp.1-15, 20th November 2016.
  15. Zeng, X., Wen, S., Zeng, Z., Huang, T., Design of memristor-based image convolution calculation in convolutional neural network. Neural Computing and Applications, pp.1–6, 18th November 2016.
  16. Zhang, S., Yu, Y., Gu, Y., Global attractivity of memristor-based fractional-order neural networks. Neurocomputing, In Press, Accepted Manuscript, 17th November 2016.
  17. Zhu, S., Wang, L., Duan, S., Memristive Pulse Coupled Neural Network with Applications in Medical Image Processing. Neurocomputing, In Press, Accepted Manuscript, 16th November 2016.
  18. Yang, J., Wang, L., Guo, T., Wang, Y., A novel memristive Hopfield neural network with application in associative memory. Neurocomputing, In Press, Accepted Manuscript, 16th November 2016.
  19. Ayana, D.G., Prusakova, V., Collini, C., Nardi, M.V., Tatti, R., Bortolotti, M., Lorenzelli, L., Chiappini, A., Chiasera, A., Ferrari, M., Lunelli, L., Dirè, S., Sol-gel synthesis and characterization of undoped and Al-doped ZnO thin films for memristive application. AIP Advances, vol.6, no.11, 15th November 2016.
  20. Caponi, S., Mattana, S., Ricci, M., Sagini, K., Juarez-Hernandez, L.J., Jimenez-Garduño, A.M., Cornella, N., Pasquardini, L., Urbanelli, L., Sassi, P., Morresi, A., Emiliani, C., Fioretto, D., Dalla Serra, M., Pederzolli, C., Iannotta, S., Macchi, P., Musio, C., A multidisciplinary approach to study the functional properties of neuron-like cell models constituting a living bio-hybrid system: SH-SY5Y cells adhering to PANI substrate. AIP Advances, vol.6, no.11, 15th November 2016.
  21. Demin, V.A., Emelyanov, A.V., Lapkin, D.A., Erokhin, V.V., Kashkarov, P.K., Kovalchuk, M.V., Neuromorphic elements and systems as the basis for the physical implementation of artificial intelligence technologies. Crystallography Reports, vol.61, no.6, pp.992–1001, 15th November 2016.
  22. Zeng, X., Li, J., Peng, F., Yang, F., A Memristor Crossbar-Based Computation System with High Precision. arXiv:1611.03264v1, [cs.ET], 10th November 2016.
  23. Abunahla, H., Mohammad, B., Homouz, D., Okelly, C.J., Modeling Valance Change Memristor Device: Oxide Thickness, Material Type, and Temperature Effects. IEEE Transactions on Circuits and Systems I: Regular Papers, pp.1-10, 10th November 2016.
  24. Dongale, T.D., Desai, N.D., Khot, K.V., Mullani, N.B., Pawar, P.S., Tikke, R.S., Patil, V.B., Waifalkar, P.P., Patil, P.B., Kamat, R.K., Patil, P.S., Bhosale, P.N., Effect of surfactants on the data directionality and learning behaviour of Al/TiO2/FTO thin film memristor-based electronic synapse. Journal of Solid State Electrochemistry, pp.1-5, 8th November 2016.
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