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Timestamp: 2019-04-25 22:50:10+00:00

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A) Joint publications (with other MemoCIS members) in international peer reviewed journals and conference.
10. C. Dias, J. Ventura. P. Aguiar, “Memristive-based neuromorphic applications and associative memories”, accepted in Memristors, Memristive Devices and Systems, Springer (2017).
11. C. Dias, H. Lv, R. Picos, P. Aguiar, S. Cardoso, P. P. Freitas, J. Ventura, “Bipolar resistive switching in Si/Ag nanostructures”, Applied Surface Science 424, 122–126 (2017).
12. E. Covi, S. Brivio, A. Serb, T. Prodromakis, M. Fanciulli, and S. Spiga, ‘Analog memristive synapse in spiking networks implementing unsupervised learning’, Front. Neurosci., vol. 10, p. 482, Oct. 2016.
13. S. Brivio, E. Covi, A. Serb, T. Prodromakis, M. Fanciulli and S. Spiga, ‘Experimental study of gradual/abrupt dynamics of HfO2-based memristive devices’, Appl. Phys. Lett., vol. 109, no. 13, p. 133504, Sep. 2016.
14. Isha Gupta, Alexantrou Serb, Ali Khiat, Ralf Zeitler, Stefano Vassanelli & Themistoklis Prodromakis, ‘Real-time encoding and compression of neuronal spikes by metal-oxide memristors’, Nature Comms, 2016.
15. D Carta, P Guttmann, A Regoutz, A Khiat, A Serb, I Gupta, A Mehonic, M Buckwell, S Hudziak, A J Kenyon and T Prodromakis, ‘X-ray spectromicroscopy investigation of soft and hard breakdown in RRAM devices’, Nanotechnology, vol. 27, 2016.
16. V. Milo, D. Ielmini, and E. Chicca, “Attractor networks and associative memories with STDP learning in RRAM synapses,” IEDM Tech. Dig. 263-266 (2017).
19. V. Milo, G. Pedretti, M. Laudato, A. Bricalli, E. Ambrosi, S. Bianchi, E. Chicca, and D. Ielmini, “Resistive switching synapses for unsupervised learning in feed-forward and recurrent neural networks,” 2018 IEEE International Symposium Circuits and Systems (ISCAS), Firenze, Italy, May 4-7, 2018.
21. G. C. Adam, R. Badulescu, S. Iordanescu, N. Wainstein, and S. Kvatinsky, "A TiO2 – Based Radio Frequency Resistive Switch," Proceedings of the International Conference on Electron, Ion, and Photon Beam Technology and Nanofabrication, June 2018 (in press).
22. A. Basu, M. F. Chang, E. Chicca, T. Karnik, H. Li, and J. S. Seo. Guest editorial low-power, adaptive neuromorphic systems: Devices, circuit, architectures and algorithms. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 8(1):1–5, 2018.
B) Related Publications in international peer reviewed journals and conference arising directly or indirectly through the COST Action.
3. S. Balatti, S. Ambrogio, R. Carboni, V. Milo, Z.-Q. Wang, A. Calderoni, N. Ramaswamy, and D. Ielmini, “Physical unbiased generation of random numbers with coupled resistive switching devices,” IEEE Trans. Electron Devices 64 (2016).
4. S. Ambrogio, S. Balatti, V. Milo, R. Carboni, Z. Wang, A. Calderoni, N. Ramaswamy, D. Ielmini, “Novel RRAM-enabled 1T1R synapse capable of low-power STDP via burst-mode communication and real-time unsupervised machine learning,” Symp. VLSI Tech. Dig. (2016).
8. L. M. Guerra, C. Dias, J. Pereira, H. Lv, S. Cardoso, P. P. Freitas, J. Ventura, “Unipolar Nonvolatile Resistive Switching in Pt/MgO/Ta/Ru Structures Deposited by Magnetron Sputtering” , accepted in J. Nanosci. Nanotech.
12. J. Xing, A. Serb, A. Khiat, R. Berdan, H. Xu and T. Prodromakis, "An FPGA-Based Instrument for En-Masse RRAM Characterization With ns Pulsing Resolution," in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 63, no. 6, pp. 818-826, June 2016.
16. Serb, A. Khiat, and T. Prodromakis, “An RRAM biasing parameter optimiser”, IEEE Trans. on Electron Devices, vol. 62, no.11, 2015.
19. R. Berdan, A. Serb, A. Khiat, A. Regoutz, C. Papavassiliou, and T. Prodromakis, “A μ-controller-based system for interfacing selector-less RRAM crossbar arrays”, IEEE Transactions on Electron Devices, vol. 62, no. 7, 2015.
20. M. Trapatseli, D. Carta, A. Regoutz, A. Khiat, A. Serb, and T. Prodromakis, “Conductive AFM investigation of switching thresholds in titanium dioxide thin films”, The Journal of Physical Chemistry C, vol. 119, no. 21, 2015.
21. Gupta, A. Serb, R. Berdan, A. Khiat, A. Regoutz and T. Prodromakis, “A cell classifier for RRAM process development”, IEEE Trans. CAS-II, vol. 62, no. 7, 2015.
22. Q. Li, A. Serb, H. Xui and T. Prodromakis, “A Memristor SPICE Model Accounting for Synaptic Activity Dependence", PLOS One, 10 (3), 2015.
23. D. Carta, G. Mountjoy, A. Regoutz, A. Khiat, A. Serb, and T. Prodromakis, “X-ray absorption spectroscopy study of TiO2-x thin films for memory applications”, The Journal of Physical Chemistry C, vol. 119, no. 8, 2015.
28. E. Covi, S. Brivio, J. Frascaroli, M. Fanciulli, S. Spiga, “(Invited) Analog HfO2-RRAM Switches for Neural Networks”, in ECS Transactions, 2016.
29. Ali Khiat, Peter Ayliffe & Themistoklis Prodromakis, ‘High Density Crossbar Arrays with Sub- 15 nm Single Cells via Liftoff Process Only’, Scientific Reports, 6, 2016.
30. Daniela Carta, Iulia Salaoru, Ali Khiat, Anna Regoutz, Christoph Mitterbauer, Nicholas M. Harrison and Themistoklis Prodromakis, “Investigation of the Switching Mechanism in TiO2‑Based RRAM: A Two-Dimensional EDX Approach”, Applied Materials & Interfaces, vol. 8, 2016.
31. Alexander Serb, Johannes Bill, Ali Khiat, Radu Berdan, Robert Legenstein & Themis Prodromakis, ‘Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses’, Nature Comms, vol. 7, 2016.
32. A. Bricalli, E. Ambrosi, M. Laudato, M. Maestro, R. Rodriguez, and D. Ielmini, “Resistive switching device technology based on silicon oxide for improved on-off ratio – Part I: Memory devices,” IEEE Trans. Electron Devices 65, 115-121 (2018). DOI: 10.1109/TED.2017.2777986.
33. A. Bricalli, E. Ambrosi, M. Laudato, M. Maestro, R. Rodriguez, and D. Ielmini, “Resistive switching device technology based on silicon oxide for improved on-off ratio – Part II: Select devices,” IEEE Trans. Electron Devices 65, 122-128 (2018). DOI: 10.1109/TED.2017.2776085.
34. S Brivio, J Frascaroli, and S Spiga, “Role of Al doping in the filament disruption in HfO2 resistance switches”, Nanotechnology 28, 395202 (2017).
39. Ioulia Tzouvadaki, Nima Aliakbarinodehi, Giovanni De Micheli, Sandro Carrara, Memristive Aptasensors for Theranostics, International Conference on Memristive Materials, Devices & Systems (MEMRISYS 2017), Athens, May, 2017.
40. C. Dias, L. Guerra, B. Bordalo, H. Lv, A. Ferraria, A. Rego, S. Cardoso, P. P. Freitas, J. Ventura, “Voltage-polarity dependent multi-mode resistive switching on sputtered MgO nanostructures”, Phys. Chem. Chem. Phys.19, 10898-10904 (2017).
41. L. Guerra, C. Dias, J. Pereira, S. Cardoso, P. P. Freitas, J. Ventura, Unipolar Nonvolatile Resistive Switching in Pt/MgO/Ta/Ru Structures Deposited by Magnetron Sputtering, J. Nanosci. Nanotechnol. 17, 564-567 (2017).
42. Jaafar AH, Gray RJ, Verrelli E, O’Neill M, Kelly SM and Kemp NT, “Reversible optical switching memristors with tunable STDP synaptic plasticity: a route to hierarchical control in artificial intelligent systems” Nanoscale, 9, 17091 (2017).
43. S. Stathopoulos, A. Khiat, M. Trapatseli, S. Cortese, A. Serb, I . Valov, and T. Prodromakis, “Multibit memory operation of metal-oxide bi-layer memristors”, Scientific Reports, vol. 7, 17532, (2017).
44. Q. Li, I. Salaoru, A. Khiat, H. Xu and T. Prodromakis, “Correlated resistive/capacitive state variability in solid TiO2 based memory devices”, Journal of Applied Physics A, vol. 123, no. 372, (2017).
45. M. Trapatseli, A. Khiat, S. Cortese, A. Serb, D. Carta and T. Prodromakis, “Impact of ultra-thin Al2O3-y layers on TiO2-x ReRAM switching characteristics”, Journal of Applied Physics, vol. 121, no. 18, (2017).
46. I. Gupta, A. Serb, R. Berdan, A. Khiat, and T. Prodromakis, “Volatility Characterisation for RRAM devices”, IEEE Electron Device letters, vol. 38, no. 1, (2017).
47. I. Gupta, A. Serb, A. Khiat, and T. Prodromakis, “Improving detection accuracy of memristor-based bio-signal sensing platform”, IEEE Trans. on Biomedical Circuits and Systems, vol. 11, no. 1, (2017).
48. A. Serb, E. Manino, I. Messaris, L. Tran-Thanh and T. Prodromakis, “Hardware-Level Bayesian Inference”, 31st Conference on Neural Information Processing Systems (NIPS), 2017.
49. A. Serb, C. Papavassiliou and T. Prodromakis, “A Memristor-CMOS Hybrid Architecture Concept for on-Line Template Matching”, Proceedings of the IEEE International Symposium on Circuits and Systems, May 2017.
50. I. Gupta, A. Serb, A. Khiat, and T. Prodromakis, “Mitigating Noise Effects in Volatile Nano-Metal Oxide Neural Detector”, Proceedings of the IEEE International Symposium on Circuits and Systems, May 2017.
51. R. Berdan, A. Serb, C. Papavassiliou and T. Prodromakis, “Live Demonstration: mNET: a Visually Rich Memristor Crossbar Simulator”, Proceedings of the IEEE International Symposium on Circuits and Systems, May 2017.
52. I. Messaris, S. Nikolaidis, A. Serb, S. Stathopoulos, I. Gupta, A. Khiat, and T. Prodromakis, “Live Demonstration: a TiO2 ReRAM Parameter Extraction Method”, Proceedings of the IEEE International Symposium on Circuits and Systems, May 2017.
53. I. Messaris, S. Nikolaidis, A. Serb, S. Stathopoulos, I. Gupta, A. Khiat, and T. Prodromakis, “A TiO2 ReRAM Parameter Extraction Method”, Proceedings of the IEEE International Symposium on Circuits and Systems, May 2017.
54. A. Khiat, P. Ayliffe and T. Prodromakis, “High Density Crossbar Arrays with Sub- 15 nm Single Cells via Liftoff Process Only”, Scientific Reports, 6, 32614, 2016.
55. A. Khiat, S. Cortese, A. Serb and T. Prodromakis, “Resistive switching of Pt/TiOx/Pt devices fabricated on flexible Parylene-C substrates”, IOP Nanotechnology, vol. 28, no. 2, 2016.
58. L. Michalas, M. Trapatseli, S. Stathopoulos, S. Cortese, A. Khiat, and T. Prodromakis, “Interface Asymmetry Induced by Symmetric Electrodes on Metal–Al:TiO–Metal Structures,” IEEE Trans. Nanotechnol., vol. 17, no. 5, pp. 867–872, Sep. 2018.
59. L. Michalas, A. Khiat, S. Stathopoulos, and T. Prodromakis, “Electrical characteristics of interfacial barriers at metal—TiO2 contacts,” J. Phys. D. Appl. Phys., vol. 51, no. 42, p. 425101, Oct. 2018.
60. L. Michalas, S. Stathopoulos, A. Khiat, and T. Prodromakis, “Conduction mechanisms at distinct resistive levels of Pt/TiO 2-x /Pt memristors,” Appl. Phys. Lett., vol. 113, no. 14, p. 143503, Oct. 2018.
61. N. Wainstein and S. Kvatinsky, "A Lumped RF Model for Nanoscale Memristive Devices and Non-Volatile Single-Pole Double-Throw Switches," IEEE Transactions on Nanotechnology, Vol. 17, No. 5, pp. 873-883, September 2018.
65. M. M. Al Chawa, C. de Benito, M. Roca, R. Picos, and S. Stavrinides, Design and implementation of passive memristor emulators using a charge-flux approach, in Circuits and Systems (ISCAS), 2018 IEEE International Symposium on . IEEE, 2018, pp. 1-5.
66. O. Camps, R. Picos, C. de Benito, M. M. Al Chawa, and S. G. Stavrinides, Emulating memristors in a digital environment using stochastic logic, in Modern Circuits and Systems Technologies (MOCAST), 2018 7th International Conference on. IEEE, 2018, pp. 1-4.
67. O. Camps, R. Picos, C. de Benito, M. M. Al Chawa, and S.G. Stavrinides, Effective accuracy estimation and representation error reduction for stochastic logic operations, in Modern Circuits and Systems Technologies (MOCAST), 2018 7 th International Conference on. IEEE, 2018, pp. 1-4.
73. M. T. McFARLANE, B ZDYRKO., Y. BANDERA, D. WORLEY, O. KLEP, M. JURČA, CH. TONKIN, S.H FOULGER, J. VILČÁKOVÁ, P. SÁHA, J. PFLEGER.: Design Rules for Carbazole Derivatized n-Alkyl Methacrylate Polymeric Memristors, Journal of Materials Chemistry C, vol. 6 (10), Dec 2018, pp. 2533-2545.
74. M. JURCA, Y. BANDERA, T. MCFARLANE, O. KLEP, D. WORLEY, J. VILČÁKOVÁ, P. SAHA, S. FOULGER: Polymer synthesis and characterization of methacrylate polymers with pendant carbazole groups, in Conf. 254th National Meeting and Exposition of the American-Chemical-Society (ACS) on Chemistry's Impact on the Global Economy Location, Washington, US, 2017, Meeting Abstract: 485.
75. T. MCFARLANE, Y. BANDERA, B. ZDYRKO, M. JURČA, O. KLEP, D WORLEY, CH. TONKIN, J. VILČÁKOVÁ, P. SAHA, S. FOULGER: Rational design of methacrylate polymers with pendant carbazole moieties for use as memristors, in Conf. 254th National Meeting and Exposition of the American-Chemical-Society (ACS) on Chemistry's Impact on the Global Economy Location: Washington, US, 2017, Meeting Abstract: 606.
76. Gina C. Adam, Ali Khiat, Themis Prodromakis, “Challenges hindering memristive neuromorphic hardware from going mainstream”, Nature Communications, 9:5267, 2018, DOI: 10.1038/s41467-018-07565-4.
2. Ascoli, R. Tetzlaff, Z. Biolek, D. Biolek, V. Biolkova, and Z. Kolka, “Techniques for reliable and accurate numerical solutions of memristor models,“ in 2015 European Conference on Circuit Theory and Design (ECCTD), Trondheim, Norway, 2015, pp. 1-4.
3. Z. Biolek, D. Biolek, V. Biolkovà, Z. Kolka, A. Ascoli, and R. Tetzlaff, “Generalized Rule of Homothety of Ideal Memristors and Their Siblings,“ in 2015 European Conference on Circuit Theory and Design (ECCTD), Trondheim, Norway, 2015, pp.1-4.
4. A. Ascoli, F. Corinto, and R. Tetzlaff, “The generalized boundary condition memristor model,” Int. J. Circuit Theory Appl., 2015, DOI: 10.1002/cta.2063.
5. A. Ascoli, F. Corinto, and R. Tetzlaff, “A class of versatile circuits, made up of standard electrical components, are memristors,” Int. J. Circuit Theory Appl., 2015, DOI: 10.1002/cta.2067.
6. A. Ascoli S. Slesazeck, H. Mähne, R. Tetzlaff, and T. Mikolajick, “Nonlinear dynamics of a locally-active memristor,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 62, no. 4, pp. 1165–1175, Apr. 2015.
12. A. Ascoli, R. Tetzlaff, and M. Biey, “Memristor and Memristor Circuit Modelling based on Methods of Nonlinear System Theory”, Springer Lecture Notes “Nonlinear Dynamics in Computational Neuroscience”, edited by F. Corinto and A. Torcini, 2016, In press.
17. E. Covi, S. Brivio, A. Serb, T. Prodromakis, M. Fanciulli, and S. Spiga, “HfO2-based Memristors for Neuromorphic Applications”, 2016 IEEE International Symposium on Circuits and Systems (ISCAS), Montreal, QC, 2016, pp. 393-396.
29. M. Potrebic, D. Tosic, and D. Biolek, “Reconfigurable microwave filters using memristor,” International Journal of Circuit Theory and Applications, Early View, First published: 15 March 2017.
32. D. Biolek, Z. Biolek, V. Biolkova, A. Ascoli, and R. Tetzlaff, “About v-i pinched hysteresis of some non-memristive systems,” Mathematical Problems in Engineering, vol. 2018, Article ID 1747865, 2018, 10 pages.
2. D. Biolek, V. Biolkova, Z. Kolka, and J. Dobes, “Analog Emulator of Genuinely Floating Memcapacitor with Piecewise- Linear Constitutive Relation,“ Circuits Systems and Signal Processing, vol. 2015, no. 4, pp. 1-20, 2015.
3. Z. Kolka, V. Biolkova, D. Biolek, and J. Vavra, “Behavioral Model for Simplified Identification of Memristor Parameters,“ in Proceedings of 2015 International Joint Conference on Neural Networks (IJCNN 2015), Killarney, Ireland, 2015, pp. 1-4.
4. D. Biolek, Z. Biolek, V. Biolkova, and Z. Kolka, “Reliable Modeling of Ideal Generic Memristors via State- Space Transformation,“ Radioengineering, vol. 24, no. 2, pp. 393-407, 2015.
5. Z. Biolek, D. Biolek, and V. Biolkova, “Differential Equations of Ideal Memristors,“ Radioengineering, vol. 24, no. 2, pp. 369-377, 2015.
6. Z. Kolka, D. Biolek, and V. Biolkova, “Improved Model of TiO2 Memristor,“ Radioengineering, vol. 24, no. 2, pp. 378-383, 2015.
7. Z. Biolek, D. Biolek, V. Biolkova, and Z. Kolka, “Comments on Pinched Hysteresis Loops of Memristive Elements,“ Radioengineering, vol. 2015, no. 4, pp. 962-967, 2015.
8. Z. Biolek, D. Biolek, and V. Biolkova, “Specification of one classical fingerprint of ideal memristor,“ Microelectronics Journal, vol. 46, no. 1, pp. 298-300, 2015.
9. Z. Biolek, D. Biolek, and V. Biolkova, “(Co) content in Circuits with Memristive Elements,“. IEEE Transactions on Circuits and Systems I- Regular Papers, vol. 62, no. 2, pp. 488-496, 2015.
10. Z. Biolek, D. Biolek, V. Biolkova, and Z. Kolka, “Variation of a classical fingerprint of ideal memristor,“ International Journal of Circuit Theory and Applications, vol. 2015, no. EV, pp. 1-5, 2015.
11. Z. Kolka, D. Biolek, and V. Biolkova, “Enhanced PSpice Model of TiO2 Memristor. International Journal of Materials, vol. 2, no. 1, pp. 25-28, 2015.
12. D. Biolek, V. Biolkova, Z. Kolka, and Z. Biolek, “Passive Fully Floating Emulator of Memristive Device for Laboratory Experiments,“ in 6th International Conference on Circuits, Systems, Control, Signals (CSCS 15), Tenerife, Spain, 2015, pp. 112-116.
13. D. Biolek, V. Biolkova, and Z. Kolka, “Memristor model for simulating large circuits for massively- parallel analog computing,“ in Proceedings of the KIT 2015, L. Mikulas, Slovakia, 2015, pp. 1-6.
44. Y. Cassuto, S. Kvatinsky, and E. Yaakobi, "Information-Theoretic Sneak Path Mitigation in Memristor Crossbar Arrays," IEEE Transaction on Information Theory, Vol. 62, No. 9, pp. 4801-4814, September 2016.
45. Y. Cassuto, S. Kvatinsky, and E. Yaakobi, “Write Sneak-Path Constraints Avoiding Disturbs in Memristor Crossbar Arrays,” Proceedings of the IEEE International Symposium on Information Theory 2016 (in press).
52. D. Biolek, Z. Biolek, and V. Biolková, “Memristive Two-Ports,” In 27th IEEE Int. Symp. on Power and Timing Modeling, Optimization and Simulation (PATMOS), Thesaloniki, Greece, 2017, pp. 1-4.
54. D. Biolek and Z. Biolek, “Predictive Models of Nanodevices,” IEEE Transactions on Nanotechnology, vol. 17, no. 5, 2018, pp. 906-913.
56. D. Biolek, V. Biolková, Z. Kolka, and J. Vávra, “Synthesis of Memristive Systems,” Journal of Telecommunication, Electronic and Computer Engineering, vol. 9, no. 2-7, 2017, pp. 171-175.
57. D. Biolek, V. Biolková, and Z. Kolka, “A Note on the So-Called Inverse Memristor,” In MEMRISYS 2017, Athens, Greece, 2017, pp. 1.
58. V. Biolková, Z. Biolek, D. Biolek, and Z. Kolka, “Voltage-Current Differential Equations of Extended Memristors with One-Dimensional State,” In IEEE Int. Conf. AMS 2017, Kota Kinabalu, Malaysia, 2017, pp. 58-62.
59. Z. Biolek, D. Biolek, and V Biolkova, “Utilization of Euler-Lagrange Equations in Circuits with Memory Elements,” Radioengineering, vol. 25, no. 4, 2016, pp. 783-789.
60. Z. Biolek and D. Biolek, “Euler-Lagrange Equations of Networks with Higher-Order Elements,” Radioengineering, vol. 26, no. 2, 2017, pp. 397-405.
66. Z. Kolka, D. Biolek, V. Biolková, and J. Vorálek, “On Digitally Emulated MemDevices,” In MEMRISYS 2017, Athens, Greece, 2017, pp. 1.
67. Z. Kolka, V. Biolková, J. Vorálek, and D. Biolek, “Digitally Emulated Electronic Devices,” In IEEE Int. Conf. AMS 2017, Kota Kinabalu, Malaysia, 2017, pp. 184-187.
69. Mladenov, V., S. Kirilov. Advanced Memristor Model with a Modified Biolek Window and a Voltage-Dependent Variable Exponent, in the Proceedings of ISTET 2017, Ilmenau, Germany, July 2017, http://www.tu-ilmenau.de/istet2017/, accepted for publication after review in peer review journal „IAPGOS“, https://e-iapgos.pl.
72. Kirilov, S., V. Mladenov. Analysis of a Passive Memristor Crossbar. – accepted after review in the peer review journal „Oriental Journal of Computer Science and Technology”, www.computerscijournal.org.
73. N. Wainstein and S. Kvatinsky, "A Lumped RF Model for Nanoscale Memristive Devices and Non-Volatile Single-Pole Double-Throw Switches," IEEE Transactions on Nanotechnology.
75. D. Biolek and Z. Biolek, “About Fingerprints of Chua’s Memristors,” IEEE Circuits and Systems Magazine, vol. 18, no. 2, 2018, pp. 35-47.
76. D. Biolek, Z. Biolek, and V. Biolkova, “Duality of Complex Systems Built from Higher-Order Elements,” Complexity, vol. 2018, accepted 9 September 2018, 24 pages.
77. D. Biolek, “Synthesis of predictive models of mem-devices,” in COST Action IC1401 Workshop, Dubrovnik, Croatia, 2018 (poster).
78. D. Biolek, Z. Biolek, V. Biolkova, and Z. Kolka, “Synthesis of Predictive Models of Nonlinear Devices: The Intutitive Approach,” in Advanced in Neural Networks and Applications (ANNA’18), Varna, Bulgaria, 2018, pp. 1-6.
79. D. Biolek, “Synthesis of predictive models of nonlinear phenomena,” in MemoCIS Workshop 8, Dresden, Germany, 2018 (invited talk).
80. V. Biolkova, J. Vavra, Z. Kolka, and D. Biolek, “Emulation of physical-based models of memristive switching devices via resistive two-port approach,” in 2nd MEM-Q workshop, Crete, Greece, 2018 (accepted).
81. Z. Biolek, D. Biolek, Z. Kolka, and V. Biolkova, “Real-World Capacitor as a Memcapacitive Element,” in New Trends in Signal Processing (NTSP), Demanova Dolina, Slovakia, 2018 (accepted).
82. Z. Kolka, V. Biolkova, and D. Biolek, “On Validity of Results of Approximate Symbolic Analysis,” in New Trends in Signal Processing (NTSP), Demanova Dolina, Slovakia, 2018 (accepted).
83. M. M. Al Chawa, C. de Benito, M. Roca, R. Picos, and S. G. Stavrinides, Design and implementation of passive memristor emulators using a charge-flux approach, in Circuits and Systems (ISCAS), 2018 IEEE International Symposium on . IEEE, 2018, pp. 1–5.
84. O. Camps, R. Picos, C. de Benito, M. M. Al Chawa, and S. G. Stavrinides, Emulating memristors in a digital environment using stochastic logic, in Modern Circuits and Systems Technologies (MOCAST), 2018 7 th International Conference on. IEEE, 2018, pp. 1–4.
85. O. Camps, R. Picos, C. de Benito, M. M. Al Chawa, and S. G. Stavrinides, Effective accuracy estimation and representation error reduction for stochastic logic operations, in Modern Circuits and Systems Technologies (MOCAST), 2018 7 th International Conference on. IEEE, 2018, pp. 1–4.
96. Mladenov, V., S. Kirilov. “Advanced Memristor Model with a Modified Biolek Window and a Voltage-Dependent Variable Exponent,”. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska (IAPGOS), 2018, vol. 8, issue 2, DOI: 10.5604/01.3001.0012.0697, pp. 15 – 20.
97. Mladenov, V., S. Kirilov. “A Nonlinear Drift Memristor Model with a Modified Biolek Window Function and Activation Threshold,” Electronics 2017, 6(4), 77; doi:10.3390/electronics6040077, pp. 1 – 15, http://www.mdpi.com/2079-9292/6/4/77.
98. Mladenov, V., S. Kirilov. “A Memristor Model with a Modified Window Function and Activation Thresholds”. IEEE Proceedings of ISCAS 2018, Florence, Italy, DOI: 10.1109/ISCAS.2018.8351429, Electronic ISSN: 2379-447X, pp. 1 – 5.
1. S. Hamdioui, L. Xie, H. A. Du Nguyen, M. Taouil, K. Bertels, H. Corporaal, H. Jiao, F. Catthoor, D. Wouters, L. Eike, and J. van Lunteren, “Memristor Based Computation-in-Memory Architecture for Data-Intensive Applications”, in Proceedings of the IEEE/ACM Conference on Design, Automation and Test in Europe, pp. 1718-1725, March 2015.
2. G. Papandroulidakis, I. Vourkas, G. C. Sirakoulis, S. Stavrinides and S. Nikolaidis, "Multi-state memristive nanocrossbar for high-radix computer arithmetic systems", 2015 IEEE 15th International Conference on Nanotechnology (IEEE-NANO), 2015.
3. R. Berdan, E. Vasilaki, A. Khiat, G. Indiveri, A. Serb and T. Prodromakis, "Emulating short-term synaptic dynamics with memristive devices", Sci. Rep., vol. 6, p. 18639, 2016.
4. H. Mostafa, A. Khiat, A. Serb, C. Mayr, G. Indiveri and T. Prodromakis, "Implementation of a spike-based perceptron learning rule using TiO2−x memristors", Front. Neurosci., vol. 9, 2015.
5. C. Dias, L. M. Guerra, J. Ventura and P. Aguiar, "Memristor-based Willshaw network: Capacity and robustness to noise in the presence of defects", Appl. Phys. Lett., vol. 106, no. 22, p. 223505, 2015.
6. I. Vourkas, D. Stathis, G. C. Sirakoulis and S. Hamdioui, "Alternative Architectures Toward Reliable Memristive Crossbar Memories", IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 24, no. 1, pp. 206-217, 2016.
7. A. Ascoli, F. Corinto, and R. Tetzlaff, “The generalized boundary condition memristor model,” Int. J. Circ. Theor. Appl., vol. 44, no. 1, pp. 60-84, 2015.
8. A. Ascoli, F. Corinto, and R. Tetzlaff, “A class of versatile circuits, made up of standard electrical components, are memristors,” Int. J. Circ. Theor. Appl., vol. 44, no. 1, pp. 127-146, 2015.
9. A. Ascoli, S. Slesazeck, H. Mähne, R. Tetzlaff, and T. Mikolajick, “Nonlinear dynamics of a locally-active memristor,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 62, no. 4, pp. 1165–1175, Apr. 2015.
10. A. Ascoli, R. Tetzlaff, S. Slesazeck, H. Mahne and T. Mikolajick, "Stability analysis supports memristor circuit design", 2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015.
11. Secco, M. Biey, F. Corinto, A. Ascoli and R. Tetzlaff, "Complex behavior in memristor circuits based on static nonlinear two-ports and dynamic bipole", 2015 European Conference on Circuit Theory and Design (ECCTD), 2015.
12. Zaher, P. Hafliger, F. Puppo, G. De Micheli and S. Carrara, "Novel readout circuit for memristive biosensors in cancer detection", 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings, 2014.
13. M. Al Chawa, R. Picos, E. Garcia-Moreno, S. Stavrinides, J. Roldan and F. Jimenez-Molinos, "An Analytical Energy Model for the Reset Transition in Unipolar Resistive-Switching RAMs", IEEE 18th Mediterranean Electrotechnical Conference (MELECON 2016), 2016.
22. I. Messaris, A. Serb, S. Stathopoulos, A. Khiat, S. Nikolaidis and T. Prodromakis, "A Data-Driven Verilog-A ReRAM Model," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018, pp. 1-1.
23. A. Serb, E. Manino, I. Messaris, L. Tran-Thanh, and T. Prodromakis, “A hardware-level Bayesian machine,” in 31st Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, CA, USA, 2017.
24. C. de Benito, M. M. A. Chawa, J. L. Rossello, M. Roca, R. Picos, I. Messaris, and S. Nikolaidis, “An analytical delay model for ReRAM memory cells,” in 2017 27th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS), Thessaloniki, Greece, 2017, pp. 1-6.
25. I. Messaris, S. Nikolaidis, A. Serb, S. Stathopoulos, I. Gupta, A. Khiat, and T. Prodromakis, “Live demonstration: A TiO2 ReRAM parameter extraction method,” in 2017 IEEE International Symposium on Circuits and Systems (ISCAS), Baltimore, MD, USA, 2017, p. 1.
26. I. Messaris, S. Nikolaidis, A. Serb, S. Stathopoulos, I. Gupta and A. Khiat and T. Prodromakis, “A TiO2 ReRAM parameter extraction method,” in 2017 IEEE International Symposium on Circuits and Systems (ISCAS), Baltimore, MD, USA, 2017, p. 1-4.
27. V. Milo, D. Ielmini, and E. Chicca, “Attractor networks and associative memories with STDP learning in RRAM synapses,” in 2017 IEEE International Electron Devices Meeting (IEDM). San Francisco, CA, USA, 2017, pp. 11.2.1 – 11.2.4.
28. S. Cortese, I. Messaris, A. Serb, A. Khiat, S. Nikolaidis and T. Prodromakis, “Impact and constraints of volatile selectors on ReRAM crossbar operation,” to be submitted in IEEE Transactions on Nanotechnology, in preparation.
29. S. Stathopoulos, A. Serb, I. Messaris, S. Nikolaidis and T. Prodromakis, “Live Demonstration: Memristor crossbar emulation based on experimentally extracted parameters,” in 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 2018, awaiting decision.
31. J. Kalomiros, S.G. Stavrinides, F. Corinto, “A two-transistor non-ideal memristor emulator,” 5th International Conference on Modern Circuits and Systems Technologies (MOCAST 2016), Thessaloniki, Greece, 2016, Article No. 7495164.
32. M. M. Al Chawa, C. de Benito, M. Roca, R. Picos, S.G. Stavrinides, “Design and implementation of passive memristor emulators using a charge-flux approach,” IEEE International Symposium on Circuits & Systems (ΙΕΕΕ-ISCAS 2018), Florence, Italy, 2018, doi: 10.1109/ISCAS.2018.8351738.
33. O. Camps, R. Picos, C. de Benito, M. M. Al Chawa, S.G. Stavrinides. “Emulating memristors in a digital environment using stochastic logic”, 7th International Conference on Modern Circuits and Systems Technologies (MOCAST 2018), Thessaloniki, Greece, 2018, doi: 10.1109/MOCAST.2018.8376637.
34. O. Camps, R. Picos, C. de Benito, M. M. Al Chawa, and S. G. Stavrinides, Effective accuracy estimation and representation error reduction for stochastic logic operations, in Modern Circuits and Systems Technologies (MOCAST), 2018 7th International Conference on. IEEE, 2018, pp. 1–4.
1. I. Klimo et al., "Modeling MIN and MAX gates using memristive devices," presented at the Workshop on Memristor Technology, Design, Automation and Computing (MemTDAC), affiliated with HiPEAC'15 conference, Amsterdam, The Netherlands, 19-21 January, 2015.
2. M.Frátrik, M. Klimo, O. Šuch and O. Škvarek, "Memristive sorting networks", physica status solidi (c), vol. 12, no. 1-2, pp. 233-237, 2015.
3. O. Such, E. Linn, M. Klimo, P. Jancovic, M. Fratrik and K. Frohlich, "On Passive Permutation Circuits", IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 5, no. 2, pp. 173-182, 2015.
4. I. Vourkas, and G. Ch. Sirakoulis, “Emerging Memristor-based Logic Circuit Design Approaches: A Review”, in IEEE Circuits and Systems Magazine, vol. 16, no. 3, pp. 15-30, thirdquarter 2016.
6. G. Papandroulidakis, I. Vourkas, and G. Ch. Sirakoulis, “Composite memristive nano-architectures with memory and in memory computing capabilities”, presented at the workshop on Memristor Technology, Design, Automation and Computing (MemTDAC) affiliated with the HiPEAC 2016 Conference, Amsterdam, The Netherlands, 18-20 January 2016.
7. International Journal of Circuit Theory and Applications (Wiley), Special Issue Call for Papers “Memristors - Devices, Models, Circuits, Systems and Applications” Guest Editors: Ronald Tetzlaff, Fernando Corinto, Rogrigo Picos, Maciej Ogorzalek.
8. F. Corinto, P. Civalleri and L. Chua, "A Theoretical Approach to Memristor Devices", IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 5, no. 2, pp. 123-132, 2015.
9. A. Theodorakakos, S. Stavrinides, E. Hatzikraniotis and R. Picos, "A non-deal memristor device", 2015 International Conference on Memristive Systems (MEMRISYS), 2015.
10. G. Papandroulidakis, I. Vourkas, G. Ch. Sirakoulis, and A. Rubio, “Heterogeneous Memristive Crossbar for In-Memory Computing,” presented at the International Conference on Memristive Systems (Memrisys 2015), Paphos, Cyprus, Greece, 8-10 November 2015.
11. G. Indiveri, E. Linn and A. Ambrogio, "ReRAM-Based Neuromorphic Computing", in Resistive Switching: From Fundamentals of Nanoionic Redox Processes to Memristive Device Applications, 1st ed., D. Ielmini and R. Waser, Ed. Weinheim, Germany: Wiley-VCH Verlag, 2016.
12. M. Nair and P. Dudek, "Gradient-descent-based learning in memristive crossbar arrays", 2015 International Joint Conference on Neural Networks (IJCNN), Killarney, pp. 1-7, 2015.
13. M. Nair and P. Dudek, "Practical gradient-descent for memristive crossbars", 2015 International Conference on Memristive Systems (MEMRISYS), 2015.
14. C. Dias, M. P. Proenca, L. Fernandes, P. B. Tavares, R. Vilarinho, J. A. Moreira, J. P. Araújo and J. Ventura, "Tuning the Stoichiometry of Ag2S Thin Films for Resistive Switching Applications", Journal of Nanoscience and Nanotechnology, vol. 16, no. 3, pp. 2608-2612, 2016.
15. C. Dias, L. M. Guerra, J. Ventura and P. Aguiar, "Memristor-based Willshaw network: Capacity and robustness to noise in the presence of defects", Appl. Phys. Lett., vol. 106, no. 22, p. 223505, 2015.
16. A. Ascoli, and R. Tetzlaff, “Analytical model for ideal generic memristor circuits based on the theory of Volterra”, Proceedings of 8. GMM/ITG/GI-Symposium Reliability by Design (ZuE), 2015.
17. A. Ascoli, V. Lanza, F. Corinto, and R. Tetzlaff, “Synchronization conditions in simple memristor neural networks”, Journal of The Franklin Institute, vol. 352, no. 8, pp. 3196-3220, 2015.
18. L. Xie, H. Nguyen, M. Taouil and K. Bertels Said Hamdioui, "Fast boolean logic mapped on memristor crossbar", 2015 33rd IEEE International Conference on Computer Design (ICCD), 2015.
19. S. Hamdioui, M. Taouil and N. Haron, "Testing Open Defects in Memristor-Based Memories", IEEE Transactions on Computers, vol. 64, no. 1, pp. 247-259, 2015.
20. H. Nguyen, L. Xie, M. Taouil, R. Nane, S. Hamdioui and K. Bertels, "Computation-in-memory based parallel adder", Proceedings of the 2015 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH´15), 2015.
21. L. Xie, H. Nguyen, M. Taouil, S. Hamdioui and K. Bertels, "Interconnect networks for memristor crossbar", Proceedings of the 2015 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH´15), 2015.
22. S. Hamdioui, L. Xie, H. Nguyen, M. Taouil, K. Bertels, H. Corporaal, H. Jiao, F. Catthoor, D. Wouters, L. Eike, J. van Lunteren, “Memristor based computation-in-memory architecture for data-intensive applications”, Proceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition (DATE ‘15), pp. 1718-1725, 2015.
23. O. Bass, A. Fish and D. Naveh, "A Memristor as Multi-Bit Memory: Feasibility Analysis", Radioengineering, vol. 24, no. 2, pp. 425-430, 2015.
24. M. Orlowski, J. Secco and F. Corinto, "Chua's Constitutive Memristor Relations for Physical Phenomena at Metal-Oxide Interfaces", IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 5, no. 2, pp. 143-152, 2015.
25. N. Wainsten and S. Kvatinsky, "An RF Memristor Model and Memristive Single-Pole Double-Throw Switches," Proceeding of the IEEE International Conference on Circuits and Systems, May 2017 (in press).
26. E. Amrany, A. Drory, and S. Kvatinsky, "Logic Design with Unipolar Memristors," Proceedings of the IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC), September 2016 (in press).
27. S. Greshnikov, E. Rosenthal, D. Soudry, and S. Kvatinsky, “A Fully Analog Memristor-Based Multilayer Neural Network with Online Backpropagation Training,” Proceeding of the IEEE International Conference on Circuits and Systems, pp. 1394-1397, May 2016.
28. MV Nair, LK Muller, G Indiveri. “A differential memristive synapse circuit for on-line learning in neuromorphic computing systems,” in Nano Futures, 2017.
29. M. Rahimi Azghadi, B. Linares-Barranco, D. Abbott, P. H.W. Leong, “A Hybrid CMOS-memristor Neuromorphic Synapse,” in IEEE Transactions on Biomedical Circuits and Systems, 2017, pp. 434-445.
30. L. Xie, H.A. Du Nguyen, J. Yu, A. Kaichouhi, M. Taouil, S. Hamdioui, “Scouting Logic: A Novel Memristor-Based Logic Design for Resistive Computing,” in IEEE Computer Society Annual Symposium on VLSI (ISVLSI 2017), Bochum, Germany, 2017.
31. L. Xie, H.A. Du Nguyen, J. Yu, M. Taouil, S. Hamdioui, “On the Robustness of Memristor Based Logic Gates,” in IEEE International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS 2017), Dresden, Germany, 2017.
32. H.A. Du Nguyen, L. Xie, M. Taouil, R. Nane, S. Hamdioui, K.L.M. Bertels, “On the Implementation of Computation-in-Memory Parallel Adder,” in IEEE Transactions On Very Large Scale Integration (VLSI) Systems (TVLSI), 2017.
33. L. Xie, H.A. Du Nguyen, M. Taouil, S. Hamdioui, K.L.M. Bertels, “A Mapping Methodology of Boolean Logic Circuits on Memristor Crossbar,” in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2017.
34. Mladenov, V., S. Kirilov. Analysis of an anti-parallel memristor circuit. – In the Proceeding of ISTET 2017, Ilmenau, Germany, July 2017, http://www.tu-ilmenau.de/istet2017/, accepted for publication after review in peer review journal „IAPGOS“, https://e-iapgos.pl.
36. Kirilov, S., V. Mladenov. Integrator Device With a Memristor Element. – accepted for publication in the Proceedings of MOCAST 2018, Thessaloniki, Greece, http://mocast.physics.auth.gr.
37. S.G. Stavrinides, “How to teach Memristors at School,” Physics Education, vol. 52, Art. No. 033008 (6pp), 2017.
40. M. Payvand, M.Nair, L. Müller, and G. Indiveri. "A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: From mitigation to exploitation." Faraday Discussions (2018).
46. F. Campabadal, A.Rodriguez-Fernandez, M.B. Gonzalez, S.G. Stavrinides, M. M. Al Chawa, R. Picos, E. Garcia-Moreno, C. de Benito, “Waveform and Frequency Effects on Reset Transition in Bipolar ReRAM in Flux-Charge Space,” IEEE International Conference on Memristive Systems (IEEE-MEMRISYS2017), Athens, Greece, 2017.
47. Mladenov, V., S. Kirilov. “Analysis of an anti-parallel memristor circuit”, Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska (IAPGOS), 2018, vol. 8, issue 2, DOI: 10.5604/01.3001.0012.0696, pp. 9 – 14.
48. Kirilov, S., V. Mladenov. “Integrator Device With a Memristor Element”. 2018 IEEE, 7th International Conference on Modern Circuits and Systems Technologies (MOCAST), Thessaloniki, Greece, DOI: 10.1109/MOCAST.2018.8376656, pp. 1 – 4.
50. Kirilov, S., V. Mladenov. “Analysis of a Passive Memristor Crossbar”. Oriental Journal of Computer Science and Technology, ISSN:0974-6471, Vol. 11, No. 1, DOI: http://dx.doi.org/10.13005/ ojcst11.01.02, pp. 4 – 11, 2018. www.computerscijournal.org.
51. Mladenov, V. „ Analysis and Simulations of Hybrid Memory Scheme Based on Memristors”, Electronics 2018, 7(11), 289; https://doi.org/ 10.3390/electronics7110289.
52. Mladenov, V. “Synthesis and Analysis of a Memristor-Based Artificial Neuron”, IEEE, CNNA 2018; The 16th International Workshop on Cellular Nanoscale Networks and their Applications Print ISBN: 978-3-8007-4766-5, pp. 1 – 4.
1. Alessandro Vallero, Ioulia Tzouvadaki, Francesca Puppo, Giovanni De Micheli, Sandro Carrara, Memristive Biosensors Integration with Microfluidic Platform, IEEE Transactions on Circuits and Systems I (TCAS I), vol. 63, no. 12, pp. 2120-2127, Dec. 2016.
4. O. Bass, A. Fish and D. Naveh, "A Memristor as Multi-Bit Memory: Feasibility Analysis", Journal of Radioengineering, vol. 24, issue 2, pp. 425-430, June 2015.
7. M. Bavandpour, H. Soleimani, B. Linares-Barranco, D. Abbott, and L. O. Chua, "Generalized Reconfigurable Memristive Dynamical System (MDS) for Neuromorphic Applications," Frontiers in Neuromorphic Engineering. Front. Neurosci. 9:409. doi: 10.3389/fnins.2015.00409. 3-Nov-2015.
11. Ioulia Tzouvadaki, X. Lu, G. De Micheli, S. Ingebrandt, S. Carrara, Nano-Fabricated Memristive Biosensors for Biomedical Applications with Liquid and Dried Samples, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, 2016, pp. 295-298.
16. G. Papandroulidakis, I. Vourkas, and G. Ch. Sirakoulis, S. Stavrinides, and S. Nikolaidis, “Multi-state Memristive Nanocrossbar for High-Radix Computer Arithmetic Systems,” presented in (IEEE NANO 2015), Rome, Italy, 27-30 July 2015.
17. I. Vourkas, D. Stathis, G. Ch. Sirakoulis, and S. Hamdioui, "Alternative Architectures Toward Reliable Memristive Crossbar Memories," IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 24, np. 1, pp. 206-217, 2016.
18. G. Ch. Sirakoulis and S. Hamdioui, “Editorial Note on Memristor Models, Circuits and Architectures,” International Journal of Unconventional Computing, vol. 12, no. 4, pp. 247-250, 2016.
19. L. V. Gambuzza, M. Frasca, L. Fortuna, V. Ntinas, I. Vourkas , and G. Ch. Sirakoulis, “A new approach based on memristor crossbar for synchronization,” 15th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2016), Dresden, Germany, 23-25 August 2016.
20. Hesham Mostafa, Ali Khiat, Alexander Serb, Christian G Mayr, Giacomo Indiveri, Themis Prodromakis, “Implementation of a spike-based perceptron learning rule using TiO2−x memristors”, In Frontiers in Neuroscience, volume 9, 2015.
21. Said Hamdioui, Shahar Kvatinsky, Gert Cauwenberghs, Lei Xie, Nimrod Wald, Siddharth Joshi, Hesham Mostafa Elsayed, Henk Corporaal, Koen Bertels, “Memristor for computing: Myth or reality?”, DATE 2017, pp. 722-731.
22. H. A. Du Nguyen, Jintao Yu, Lei Xie, Mottaqiallah Taouil, Said Hamdioui, Dietmar Fey, “Memristive devices for computing: Beyond CMOS and beyond von Neumann”, VLSI-SoC 2017, pp. 1-10.
23. Serb, A. Corna, R. George, A. Khiat, F. Rocchi, M. Reato, M. Maschietto, C. Mayr, G. Indiveri, S. Vassanelli, et al. "A geographically distributed bio-hybrid neural network with memristive plasticity," arXiv preprint arXiv:1709.04179, 2017.
26. C. Mohan, L.A. Camuñas-Mesa, E. Vianello, L. Periniolla, C. Reita, J.M. de la Rosa, T. Serrano-Gotarredona, B. Linares-Barranco, “Calibration of offset via bulk for low-power HfO2 based 1T1R memristive crossbar read-out system,” Microelectronic Engineering, Volume 198, 2018, Pages 35-47.
27. V. Milo, G. Pedretti, M. Laudato, A. Bricalli, E. Ambrosi, S. Bianchi, E. Chicca, and D. Ielmini. Resistive switching synapses for unsupervised learning in feed-forward and recurrent neural networks. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS), pages 1–5. IEEE, 2018.
29. M. M. Al Chawa, C. de Benito, M. Roca, R. Picos, S.G. Stavrinides, “Design and implementation of passive memristor emulators using a charge-flux approach,” IEEE International Symposium on Circuits & Systems (ΙΕΕΕ-ISCAS 2018), Florence, Italy, 2018, doi: 10.1109/ISCAS.2018.8351738.
30. O. Camps, R. Picos, C. de Benito, M. M. Al Chawa, S.G. Stavrinides. “Emulating memristors in a digital environment using stochastic logic” ,” 7th International Conference on Modern Circuits and Systems Technologies (MOCAST 2018), Thessaloniki, Greece, 2018, doi: 10.1109/MOCAST.2018.8376637.
1. I. Vourkas, D. Stathis, and G. Ch. Sirakoulis, “Massively Parallel Analog Computing: Ariadne’s Thread Was Made of Memristors,” in IEEE Transactions on Emerging Topics in Computing, vol.PP, no.99, pp.1-1, doi: 10.1109/TETC.2015.2420353.
2. V. Ntinas, I. Vourkas, G. Ch. Sirakoulis, and A. I. Adamatzky, "Oscillation-Based Slime Mould Electronic Circuit Model for Maze-Solving Computations," in IEEE Transactions on Circuits and Systems I: Regular Papers, vol.PP, no.99, pp.1-12, doi: 10.1109/TCSI.2016.2566278.
3. I. Vourkas, G. Papandroulidakis, G. Ch. Sirakoulis, and A. Abusleme, “2T1M-Based Double Memristive Crossbar Architecture for In-Memory Computing,” International Journal of Unconventional Computing, vol. 12, no. 4, pp. 265-280, 2016.
4. G. Papandroulidakis, I. Vourkas, and G. Ch. Sirakoulis, “Composite memristive nano-architectures with memory and in memory computing capabilities,” presented in workshop on Memristor Technology, Design, Automation and Computing (MemTDAC) affiliated with the HiPEAC 2016 Conference, Amsterdam, Netherlands, 18-20 January 2016.
6. I. Vourkas, A. Abusleme, V. Ntinas, G. Ch Sirakoulis, and A. Rubio, "A Digital Memristor Emulator for FPGA-Based Artificial Neural Networks," presented in Verification and Security IEEE International Workshop (IVSW), Catalunya, Spain, July 4-6, 2016, pp. 1-4.
7. I. Vourkas, A. Abusleme, G. Ch Sirakoulis, and A. Rubio, "1-D Memristor Networks as Ternary Storage Cells," 15th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2016), Dresden, Germany, 23-25 August 2016.
8. S. Zuin, M. Escudero López, F. Moll, A. Rubio, I. Vourkas and G. Ch. Sirakoulis, "Experience on Material Implication Computing with an Electromechanical Memristor Emulator," accepted for presentation in 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016), 6-9 December 2016, Athens, Greece.
9. M. Rahimi Azghadi, B. Linares-Barranco, D. Abbott, P. H.W. Leong, "A Hybrid CMOS memristor Neuromorphic Synapse," IEEE Trans. on Biomedical Circuits and Systems, in Press.
10. H. Mostafa, C. Mayr, G. Indiveri, “Beyond Spike-Timing Dependent Plasticity in Memristor Crossbar Arrays”, In International Symposium on Circuits and Systems, (ISCAS), 2016, IEEE, 2016.
11. R. George, C. Mayr, G. Indiveri, S. Vassanelli , “Event-based softcore processor in a biohybrid setup applied to structural plasticity”, In Event-based Control, Communication, and Signal Processing (EBCCSP), 2015 International Conference on, 2015.
16. Ioulia Tzouvadaki, X. Lu, G. De Micheli, S. Ingebrandt, S. Carrara, Nano-Fabricated Memristive Biosensors for Biomedical Applications with Liquid and Dried Samples, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, 2016, pp. 295-298. doi: 10.1109/EMBC.2016.7590698.
19. N. Talati, S. Gupta, P. Mane, and S. Kvatinsky, “Logic Design within Memristive Memories Using Memristor Aided loGIC (MAGIC),”IEEE Transactions on Nanotechnology, Vol. 15, No. 4, pp. 635-650, July 2016.
20. L. Azriel and S. Kvatinsky, "Towards a Memristive Hardware Secure Hash Function (MemHash)", Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust (HOST), May 2017 (in press).
21. R. Ben-Hur and S. Kvatinsky, "Memristive Memory Processing Unit (MPU) Controller for In-Memory Processing", Proceedings of the IEEE International Conference on Science of Electrical Engineering, November 2016.
22. R. Ben-Hur, N. Talati, and S. Kvatinsky, "Algorithmic Considerations in Memristive Memory Processing Units (MPU)," Proceedings of the International Cellular Nanoscale Networks and their Applications, August 2016 (in press).
23. R. Ben-Hur and S. Kvatinsky, "Memory Processing Unit for In-Memory Processing," Proceedings of the IEEE/ACM International Symposium on Nanoscale Architectures, July 2016 (in press).
24. H. Abu Hanna, L. Danial, S. Kvatinsky, and R. Daniel, "Modeling Biochemical Reactions and Gene Networks with Memristors," Proceeding of the IEEE Symposium on Biological Circuits and Systems, October 2017.
25. J. Yu, R. Nane, I. Ashraf, M. Taouil, S. Hamdioui, H. Corporaal, K.L.M. Bertels, “Skeleton-based Synthesis Flow for Computation-In-Memory Architectures”, IEEE Transactions on Emerging Topics in Computing, October 2017.
26. L. Danial, N. Wainstein, S. Kraus, and S. Kvatinsky, "DIDACTIC: A Data-Intelligent Digital-to-Analog Converter with a Trainable Integrated Circuit using Memristors," IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2017.
27. Dozortsev, I. Goldshtein, S. Kvatinsky, "Analysis of the row grounding technique in a memristor-based crossbar array," Int. J. of Circ. Theory and Applications, Nov. 2017.
28. M. Rahimi Azghadi, B. Linares-Barranco, D. Abbott, P. H.W. Leong, "A Hybrid CMOS-memristor Neuromorphic Synapse," IEEE Trans. on Biomedical Circuits and Systems, vol. 11, No. 2, pp. 434-445 , April 2017.
29. J. Vavra, D. Biolek, "AN ENVELOPE DETECTOR BASED ON MEMRISTIVE SYSTEMS," Journal of Telecommunication, Electronic and Computer Engineering, vol. 9, No. 2-7, pp. 183-186, 2017.
30. N. Wainsten and S. Kvatinsky, "An RF Memristor Model and Memristive Single-Pole Double Throw Switches," Proceeding of the IEEE International Symposium on Circuits and Systems, May 2017.
31 M. Zidan, A. Chen, G. Indiveri, and W. Lu, "Memristive computing devices and applications," Journal of Electroceramics, Springer, pp. 1-17, 2017.
32. L. Azriel and S. Kvatinsky, "Towards a Memristive Hardware Secure Hash Function (MemHash)", Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust (HOST), May 2017.
33. M. Nair, L. Muller, G. Indiveri, "A differential memristive synapse circuit for on-line learning in neuromorphic computing systems," Nano Futures, vol. 1, No. 3, pp. 035003, IOP Publishing, 2017.
34. I. Tzouvadaki, N. Aliakbarinodehi, G. De Micheli, and S. Carrara, "Memristive Effect as a Novelty in Drug Monitoring," Nanoscale, 2017.
35. M. Barbareschi, A. Bosio, H.A. Du Nguyen, S. Hamdioui, M. Traiola, E. I. Vatajelu, “ Memristive devices: Technology, Design Automation and Computing Frontiers”, 12th International Conference on Design &Technology of Integrated Systems in Nanoscale Era (DTIS 2017), 4-6 April 2017, pp. 1-8.
36. C. Mohan, T. Serrano-Gotarredona, E. Vianello, L. Periniolla, C. Reita, J.M. de la Rosa, and B. Linares-Barranco, "On the Use of Offset Calibration Techniques for Low-Power Memristor Arrays Read-Out," International Conference on Memristive Materials, Devices & Systems (MEMRISYS 2017).
37. S. Kvatinsky, R. Ben-Hur, N. Talati, and N. Wald, "mMPU: Memristive Memory Processing Unit," International Conference on Memristive Materials, Devices & Systems, April 2017.
38. M. Klimo and O. Such, "Memristive Implementation of Fuzzy Logic for Cognitive Computing," FUTURE COMPUTING, 2017: The Ninth International Conference on Future Computational Technologies and Applications. Athens, Feb. 2017.
39. R. Hur, N. Wald, N. Talati, and S. Kvatinsky, "SIMPLE MAGIC: Synthesis and In-memory MaP-ping of Logic Execution for Memristor-Aided loGIC," ICCAD 2017.
40. J. Reuben, R. Ben-Hur, N. Wald, N. Talati, A. Ali, P.-E. Gaillardon, and S. Kvatinsky, "Memristive logic: A framework for evaluation and comparison," IEEE 27th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS), 2017.
41. S. Naus, I. Tzouvadaki, P.-E. Gaillardon, A. Biscontini, G. De Micheli, and C. Sandro, "An efficient electronic measurement interface for memristive biosensors," 2017 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1-4, 2017.
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55. Charly Meyer, André Chanthbouala, Jean Tomas, Vincent Garcia, Manuel Bibes, Stéphane Fusil, Julie Grollier, Sylvain Saïghi, “Verilog-A model of ferroelectric memristors dedicated to neuromorphic designers,” ICECS 2018, 10-12 Dec. 2018, Bordeaux, France.
56. Elisa Vianello, Denys R. B. Ly, Selina La Berbera, Gabriele Navarro, Niccolo Castellani, Olga Cueto, Guillame Bourgeois, Damien Querlioz, Etienne Nowak, “Phase Change Memory and Metal Oxide Resistive Memory as Artificial Synapses in Spiking Neural Networks,” ICECS 2018, 10-12 Dec. 2018, Bordeaux, France.
57. Oscar Camps, Mohamad Moner Al Chawa, Carol de Benito, Miquel Roca, Stavros G. Stavrinides, Rodrigo Picos, Leon O. Chua, “A Purely Digital Memristor Emulator based on a Flux-Charge Model,” ICECS 2018, 10-12 Dec. 2018, Bordeaux, France.
58. Pablo Negri, B. Linares-Barranco, and T. Serrano-Gotarredona, “Scene Context Analysis for Event-Driven Spike-Based Deep Neural Networks,” ICECS 2018, 10-12 Dec. 2018, Bordeaux, France.
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