Single pairing spike-timing dependent plasticity in BiFeO3memristors with a time window of 25 ms to 125 μs

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Nan Du - , Chemnitz University of Technology (Author)
  • Mahdi Kiani - , Chemnitz University of Technology (Author)
  • Christian G. Mayr - , University of Zurich (Author)
  • Tiangui You - , Chemnitz University of Technology (Author)
  • Danilo Bürger - , Chemnitz University of Technology (Author)
  • Ilona Skorupa - , Chemnitz University of Technology, Helmholtz-Zentrum Dresden-Rossendorf (Author)
  • Oliver G. Schmidt - , Chemnitz University of Technology, Leibniz Institute for Solid State and Materials Research Dresden (Author)
  • Heidemarie Schmidt - , Chemnitz University of Technology (Author)

Abstract

Memristive devices are popular among neuromorphic engineers for their ability to emulate forms of spike-driven synaptic plasticity by applying specific voltage and current waveforms at their two terminals. In this paper, we investigate spike-timing dependent plasticity (STDP) with a single pairing of one presynaptic voltage spike and one post-synaptic voltage spike in a BiFeO3memristive device. In most memristive materials the learning window is primarily a function of the material characteristics and not of the applied waveform. In contrast, we show that the analog resistive switching of the developed artificial synapses allows to adjust the learning time constant of the STDP function from 25 ms to 125 μs via the duration of applied voltage spikes. Also, as the induced weight change may degrade, we investigate the remanence of the resistance change for several hours after analog resistive switching, thus emulating the processes expected in biological synapses. As the power consumption is a major constraint in neuromorphic circuits, we show methods to reduce the consumed energy per setting pulse to only 4.5 pJ in the developed artificial synapses.

Details

Original languageEnglish
Article number227
Journal Frontiers in neuroscience
Volume9
Issue numberJUN
Publication statusPublished - 2015
Peer-reviewedYes
Externally publishedYes

Keywords

ASJC Scopus subject areas

Keywords

  • Artificial synapse, BiFeO memristor, Learning window, Low-power device, Memory consolidation, Single pairing STDP