References
97
89. E. Covi, S. Brivio, A. Serb, T. Prodromakis, M. Fanciulli, S. Spiga, Analog memristive
synapse in spiking networks implementing unsupervised learning. Front. Neurosci. 10, 482
(2016)
90. I. Gupta, A. Serb, A. Khiat, R. Zeitler, S. Vassanelli, T. Prodromakis, Real-time encoding and
compression of neuronal spikes by metal-oxide memristors. Nat. Commun. 7, 12805 (2016)
91. V. Milo, D. Ielmini, E. Chicca, Attractor networks and associative memories with STDP
learning in RRAM synapses, in 2017 IEEE International Electron Devices Meeting (IEEE,
Piscataway, 2017), pp. 11.2.1–11.2.4
92. F. Corinto, M. Forti, Complex dynamics in arrays of memristor oscillators via the flux–charge
method. IEEE Trans. Circuits Syst. I Regul. Pap. 65(3), 1040–1050 (2017)
93. S. Balatti, S. Ambrogio, R. Carboni, V. Milo, Z. Wang, A. Calderoni, N. Ramaswamy, D.
Ielmini, Physical unbiased generation of random numbers with coupled resistive switching
devices. IEEE Trans. Electron Dev. 63(5), 2029–2035 (2016)
94. R. Berdan, E. Vasilaki, A. Khiat, G. Indiveri, A. Serb, T. Prodromakis, Emulating short-term
synaptic dynamics with memristive devices. Sci. Rep. 6, 18639 (2016)
95. H.A. Hanna, L. Danial, S. Kvatinsky, R. Daniel, Modeling biochemical reactions and gene
networks with memristors, in 2017 IEEE Biomedical Circuits and Systems Conference (IEEE,
Piscataway, 2017), pp. 1–4
96. V. Ntinas, I. Vourkas, G.C. Sirakoulis, A.I. Adamatzky, Oscillation-based slime mould
electronic circuit model for maze-solving computations. IEEE Trans. Circuits Syst. I Regul.
Pap. 64(6), 1552–1563 (2017)
97. C. Sichonidis, I. Vourkas, N. Mitianoudis, G.C. Sirakoulis, A memristive circular buffer for
real-time signal processing, in 2016 5th International Conference on Modern Circuits and
Systems Technologies (IEEE, Piscataway, 2016), pp. 1–4
98. Z. Lv, Y. Zhou, S.-T. Han, V. Roy, From biomaterial-based data storage to bio-inspired
artificial synapse. Mater. Today 21(5), 537–552 (2018)
99. S. Pi, C. Li, H. Jiang, W. Xia, H. Xin, J.J. Yang, Q. Xia, Memristor crossbar arrays with 6-nm
half-pitch and 2-nm critical dimension. Nat. Nanotechnol. 14(1), 35 (2019)
100. Y. Li, Z. Wang, R. Midya, Q. Xia, J. Yang, Review of memristor devices in neuromorphic
computing: materials sciences and device challenges. J. Phys. D Appl. Phys. 51(50), 503002
(2018)
101. S. Carrara, D. Sacchetto, M.-A. Doucey, C. Baj-Rossi, G. De Micheli, Y. Leblebici,
Memristive-biosensors: a new detection method by using nanofabricated memristors. Sensors
Actuators B Chem. 171, 449–457 (2012)
102. I. Tzouvadaki, N. Aliakbarinodehi, G. De Micheli, S. Carrara, The memristive effect as a
novelty in drug monitoring. Nanoscale 9(27), 9676–9684 (2017)
103. I. Tzouvadaki, P. Jolly, X. Lu, S. Ingebrandt, G. De Micheli, P. Estrela, S. Carrara, Label-free
ultrasensitive memristive aptasensor. Nano Lett. 16(7), 4472–4476 (2016)
104. N. Wainstein, S. Kvatinsky, TIME-tunable inductors using memristors. IEEE Trans. Circuits
Syst. I Regul. Pap. 65(5), 1505–1515 (2017)
Précédent

- 128/463

Suivant