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Improved Synaptic Behavior of CBRAM Using Internal Voltage Divider for Neuromorphic Systems.
- Source :
-
IEEE Transactions on Electron Devices . Sep2018, Vol. 65 Issue 9, p3976-3981. 6p. - Publication Year :
- 2018
-
Abstract
- In this paper, we demonstrate the linear conductance-change characteristics of a conductive-bridging RAM (CBRAM) to be employed as an artificial synapse device in neuromorphic systems. The CBRAM with a bilayer electrolyte structure (${\mathrm {Cu/Cu}}_{{2}-{x}}\text{S}$ / $\mathrm {WO}_{{3}-{x}}$ /W) exhibits analog switching behavior during the depression process due to the well-controlled dissolution of the conductive filament. To analyze the origin of this motion, we investigate the effective voltage applied to $\mathrm {Cu}_{{2}-{x}}\text{S}$ and $\mathrm {WO}_{{3}-{x}}$. Our findings reveal that $\mathrm {Cu}_{{2}-{x}}\text{S}$ , acting as a voltage divider, helps in suppressing the large voltage drop in $\mathrm {WO}_{{3}-{x}}$ , where the formation/dissolution of filament occurs. Furthermore, due to the diode-like characteristics of $\mathrm {Cu}_{{2}-{x}}\text{S}$ and the division of voltage drop between $\mathrm {WO}_{{3}-{x}}$ and $\mathrm {Cu}_{{2}-{x}}\text{S}$ , an optimum programming energy is applied to $\mathrm {WO}_{{3}-{x}}$ during the depression process. This leads to linear conductance-change characteristics under identical pulses. However, abrupt conductance-change characteristics are observed during the potentiation process. Thus, we use only the device characteristics of the depression part for the neuromorphic system. An excellent classification accuracy is achieved due to the linear conductance-change characteristics and optimized pulse conditions. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ELECTRIC potential
*MICROELECTROMECHANICAL systems
Subjects
Details
- Language :
- English
- ISSN :
- 00189383
- Volume :
- 65
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Electron Devices
- Publication Type :
- Academic Journal
- Accession number :
- 132684463
- Full Text :
- https://doi.org/10.1109/TED.2018.2857494