Stochasticity Modeling in Memristors

被引:87
作者
Naous, Rawan [1 ]
Al-Shedivat, Maruan [2 ]
Salama, Khaled Nabil [1 ]
机构
[1] King Abdullah Univ Sci & Technol, Comp Elect Math Sci & Engn Div, Thuwal 23955, Saudi Arabia
[2] Carnegie Mellon Univ, Machine Learning Dept, Pittsburgh, PA 15213 USA
关键词
Memristor; memristor model; neuromorphics; stochasticity; stochastic electronics; threshold-based devices; RESISTIVE-SWITCHING MEMORY; SPICE MODEL; DEVICES; DESIGN; ELECTRONICS; PARADIGM; READOUT;
D O I
10.1109/TNANO.2015.2493960
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on nondeterministic memristor logic.
引用
收藏
页码:15 / 28
页数:14
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