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Memristor SPICE Model Simulation and Device Hardware Correlation

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Cybersecurity Systems for Human Cognition Augmentation

Part of the book series: Advances in Information Security ((ADIS,volume 61))

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Abstract

The memristor device was first described in 1971 by Leon Chua [1] as the fourth basic circuit element. Recently, the memristor has received much attention since the publication of the paper titled “The missing memristor found” in 2008 describing the memristive characteristics of metal-oxide-based memristor devices [2]. The memristor name is a contraction for memory resistor [1]. It is a two terminal passive device whose resistance state depends on its previous state. Given their two terminal structural simplicity and electronic passivity, the applications for memristor technology range from non-volatile memory, instant on computers, reconfigurable electronics and neuromorphic computing [3, 4]. Several device models have been presented to describe the electrical behavior of memristor devices [1, 2, 4–6]. However, there is no paper to the best of our knowledge in the published literature that shows model versus hardware plot correlations within a SPICE microelectronics industry standard environment. Recently, we developed an empirical model that accurately describes the electrical behavior of ion-conductor chalcogenide-based memristors [7]. In this work, we present a SPICE-based version of our memristor device compact model.

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References

  1. L. Chua, “Memristor - The Missing Circuit Element,” IEEE Transactions on Circuits Theory (IEEE), vol. 18, no. 5, 1971, pp. 507–519.

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  7. R.E. Pino, J.W. Bohl, N. McDonald, B. Wysocki, P. Rozwood, K.A. Campbell, A.S. Oblea, and A. Timilsina, “Compact Method for Modeling and Simulation of Chalcogenide Based Memristor Devices,” IEEE/ACM International Symposium on Nanoscale Architectures 2010, Anaheim, CA, June 17-18, 2010.

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Correspondence to Robinson E. Pino .

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Pino, R.E., Oblea, A.S., Campbell, K.A. (2014). Memristor SPICE Model Simulation and Device Hardware Correlation. In: Pino, R., Kott, A., Shevenell, M. (eds) Cybersecurity Systems for Human Cognition Augmentation. Advances in Information Security, vol 61. Springer, Cham. https://doi.org/10.1007/978-3-319-10374-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-10374-7_11

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