Crossbar Array Programming Using Piecewise-Constant Signals
https://doi.org/10.25682/NIISI.2025.3.0002
Аннотация
To program a crossbar array, we need to adjust the resistor conductance using a limited number of
control signals, which are voltages applied to the crossbar lines. Since the number of lines is significantly smaller than
the number of resistors, this is a multi-step procedure. At each step, the conductances of the selected resistors are
adjusted. The number of such resistors is no greater than the number of control signals. This inevitably changes the
conductivity of some half-selected resistors, too. These unwanted changes must be compensated for. We examined a
crossbar programming procedure using high-frequency piecewise-constant control signals. Our analysis involved a
simple resistive element model. We demonstrated that an arbitrary (within known limits) conductance matrix can be
programmed. At each step, a row or column of the crossbar array is generated or adjusted. We discussed the feasibility
and convenience of such a procedure
Об авторах
G. A. Beskhlebnova
Scientific Research Institute for System Analysis of the National Research Centre Kurchatov Institute
Россия
Россия
V. B. Kotov
Scientific Research Institute for System Analysis of the National Research Centre Kurchatov Institute
Россия
Россия
Список литературы
1. Kotov V.B., Beskhlebnova G.A. Specifics of Crossbar Resistor Arrays. // B. Kryzhanovsky et
2. al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research
3. VI (NEUROINFORMATICS 2022). Studies in Computational Intelligence. Vol. 1064. Cham: Springer.
4. PP. 292–304. https://doi.org/10.1007/978-3-031-19032-2_31.
5. Adamatzky A., Chua L. Memristor Networks. Springer International Publishing (2014).
6. Advances in Memristors, Memristive Devices and Systems. / Edited by S. Vaidyanathan and
7. C. Volos. Springer International Publishing AG (2017).
8. Kim S. Ju, Kim S., Jang H.W. Competing memristors for brain-inspired computing. iScience 24,
9. , January 22, 2021.
10. Kotov V.B., Beskhlebnova G.A. Generation of the Conductivity Matrix. // B. Kryzhanovsky et al.
11. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research
12. V (NEUROINFORMATICS 2021). Studies in Computational Intelligence. Vol. 1008. Cham: Springer.
13. PP. 276-284.
14. Surazhevsky I.A. at all. Noise-assisted persistence and recovery of memory state in a memristive
15. spiking neuromorphic network.Chaos, Solitons and Fractals. 146 (2021). 110890.
16. Beskhlebnova G.A., Kotov V.B. The Variable Resistor Under a High-Frequency Signal.
17. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive
18. Research VII (NEUROINFORMATICS 2023). Studies in Computational Intelligence. Vol. 1120. Springer
19. Nature Switzerland AG. 2023. PP. 257–266. https://doi.org/10.1007/978-3-031-44865-2_28.
20. Kotov V.B., Beskhlebnova G.A. Use of High-Frequency Signals to Generate a Conductivity
21. Matrix. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and
22. Cognitive Research VIII (NEUROINFORMATICS 2024). Studies in Computational Intelligence.
23. Vol. 1179. Springer Nature Switzerland AG. 2025. PP. 265-272.
24. Kotov V.B., Beskhlebnova G.A. Local Point Recording of Information into a Crossbar Resistor
25. Array // SRISA Proceedings. Vol. 14. No. 4 Pp. 33–40 (in Russ.)
26. Kotov V.B., Yudkin F.A. Modeling and Characterization of Resistor Elements for Neuromorphic
27. Systems. Optical Memory and Neural Networks (Information Optics). 2019, v.28, No.4, P. 271-282.
28. V.B. Kotov, Z. B. Sokhova. Two-frequency recording of information into a resistor array.
29. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive
30. Research IX (NEUROINFORMATICS 2025). Studies in Computational Intelligence. Vol. 1241. Springer
31. Nature Switzerland AG. 2026. PP. 463-476.
Рецензия
Для цитирования:
Beskhlebnova G.A., Kotov V.B. Crossbar Array Programming Using Piecewise-Constant Signals. Труды НИИСИ. 2025;15(3):17-22. https://doi.org/10.25682/NIISI.2025.3.0002
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