Stochastic Memristor Model

sensorsLab_tools_StochasticMem.gif

We developed a stochastic model of memristor devices. 

Innate stochasticity is modeled in a circuit compatible format and incorporated into models of threshold based memristors covering a wide set of designs. Experimental fitting to fabricated devices highlights the modeling accuracy and the generalized form of behavior. 

Feel free to use/modify these codes as you see fit. Any publications  (codes, papers, technical reports,..) in which our codes (in their original or a modified format) have been used should cite the following references.    
  • Rawan Naous, Maruan Al-Shedivat, and Khaled Nabil Salama, Stochasticity Modeling in MemristorsIEEE Transactions on Nanotechnology (TNANO), vol. 15, no. 1, pp. 15-28, 2016 DOI:10.1109/TNANO.2015.2493960
  • Maruan Al-Shedivat, Rawan Naous,Gert Cauwenberghs, and Khaled Nabil Salama, Memristors Empower Spiking Neurons with Stochasticity, IEEE Journal of Emerging technologies in circuits and systems, VOL. 5, NO. 2, 242-253, JUNE 2015        
Copyright (c) 2015, Rawan Naous, Maruan Al-Shedivat, Khaled Nabil Salama                   
King Abdullah University of Science and Technology
All rights reserved.
Last Update: 9-Nov-2015; run using run using spectre version 11.1.0.509.isr    cadence version 2012.09  
 
For the developed tools, click here.