Scholars@Duke publication: The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design

The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design

Publication , Conference

Hu, M; Wang, Y; Qiu, Q; Chen, Y; Li, H

Published in: Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC

March 27, 2014

Memristor, the fourth basic circuit element, has shown great potential in neuromorphic circuit design for its unique synapse-like feature. However, though the continuous resistance state of memristor has been expected, obtaining and maintaining an arbitrary intermediate state cannot be well controlled in nowadays memristive system. In addition, the stochastic switching behaviors have been widely observed. To facilitate the investigation on memristor-based hardware implementation, we built a stochastic behavior model of TiO2 memristive devices based on the real experimental results. By leveraging the stochastic behavior of memristors, a macro cell design composed of multiple parallel connecting memristors can be successfully used in implementing the weight storage unit and the stochastic neuron - the two fundamental components in neural network (NN)s, providing a feasible solution in memristor-based hardware implementation. © 2014 IEEE.

Duke Scholars

Author Yiran Chen Electrical and Computer Engineering

Author Hai "Helen" Li Electrical and Computer Engineering

Published In

Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC

DOI

10.1109/ASPDAC.2014.6742993

Publication Date

March 27, 2014

Start / End Page

831 / 836

Citation

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Hu, M., Wang, Y., Qiu, Q., Chen, Y., & Li, H. (2014). The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design. In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC (pp. 831–836). https://doi.org/10.1109/ASPDAC.2014.6742993

Hu, M., Y. Wang, Q. Qiu, Y. Chen, and H. Li. “The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 831–36, 2014. https://doi.org/10.1109/ASPDAC.2014.6742993.

Hu M, Wang Y, Qiu Q, Chen Y, Li H. The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design. In: Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC. 2014. p. 831–6.

Hu, M., et al. “The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design.” Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 2014, pp. 831–36. Scopus, doi:10.1109/ASPDAC.2014.6742993.

Hu M, Wang Y, Qiu Q, Chen Y, Li H. The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design. Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC. 2014. p. 831–836.

Published In

Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC

DOI

10.1109/ASPDAC.2014.6742993

Publication Date

March 27, 2014

Start / End Page

831 / 836