Switching Dynamics in Vanadium Dioxide-Based Stochastic Thermal Neurons
- Purdue Univ., West Lafayette, IN (United States)
- Penn State Univ., State College, PA (United States)
- Purdue Univ., West Lafayette, IN (United States); Indian Inst. of Technology, Mumbai (India)
We report on switching dynamics of individual and coupled vanadium dioxide (VO2) devices subject to voltage pulses as the temperature is systematically varied from room temperature spanning the insulator–metal transition (IMT) temperature. The switching voltage of single devices has a strong relationship with both temperature and voltage pulsewidth. Two-step switching in connected VO2 devices has been noted in current transient plots and was found to depend on temperature, pulsewidth, and pulse amplitude. Experimental switching behavior measured from VO2 artificial neurons was implemented into a spiking neural network (SNN). During training, modulating the switching voltage via temperature affords a novel method to implement homeostasis with the coupled devices. Simulation results show the efficacy of the stochastic neuronal characteristics and the proposed homeostasis mechanism on a standard digit recognition task. As a result, these studies contribute to ongoing efforts in neuromorphic computing exploiting collective phase transitions.
- Research Organization:
- Pennsylvania State Univ., University Park, PA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Basic Energy Sciences (BES)
- Grant/Contract Number:
- SC0021118
- OSTI ID:
- 1961583
- Journal Information:
- IEEE Transactions on Electron Devices, Vol. 69, Issue 6; ISSN 0018-9383
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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