Emulation of spike-timing dependent plasticity in nano-scale phase change memory

Dae Hwan Kang, Hyun Goo Jun, Kyung Chang Ryoo, Hongsik Jeong, Hyunchul Sohn

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The spike-timing dependent plasticity (STDP) of biological synapses, which is known to be a function of the formulated Hebbian learning rule of human cognition, learning and memory abilities, was emulated with two-phase change memory (2-PCM) cells built with 39. nm technology. For this, we designed a novel time-modulated voltage (TMV) scheme for changing the conductance of 2-PCM cells, that could produce both long-term potentiation (LTP) and long-term depression (LTD) by applying variable (decreasing/increasing) pulse voltages according to the sign and magnitude in time interval between pre- and post-spikes. Since such schemes can be easily modified to have a variety of pulse shapes and time intervals between pulses, it is expected to be a proper scheme for designing diverse synaptic connection abilities. In addition, the small form factor and low energy consumption of 2-PCM make them comparable to biological synapses, which makes phase change memory a promising candidate for electronic synapses in large-scale neuromorphic system applications.

Original languageEnglish
Pages (from-to)153-158
Number of pages6
JournalNeurocomputing
Volume155
DOIs
Publication statusPublished - 2015 May 1

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Emulation of spike-timing dependent plasticity in nano-scale phase change memory'. Together they form a unique fingerprint.

  • Cite this