Enabling an Integrated Rate-temporal Learning Scheme on Memristor

Enabling an Integrated Rate-temporal Learning Scheme on Memristor
Title:
Enabling an Integrated Rate-temporal Learning Scheme on Memristor
Other Titles:
Scientific Reports
Keywords:
Publication Date:
23 April 2014
Citation:
Abstract:
Learning scheme is the key to the utilization of spike-based computation and the emulation of neural/ synaptic behaviors toward realization of cognition. The biological observations reveal an integrated spike time- and spike rate-dependent plasticity as a function of presynaptic firing frequency. However, this integrated rate-temporal learning scheme has not been realized on any nano devices. In this paper, such scheme is successfully demonstrated on a memristor. Great robustness against the spiking rate fluctuation is achieved by waveform engineering with the aid of good analog properties exhibited by the iron oxide-based memristor. The spike-time-dependence plasticity (STDP) occurs at moderate presynaptic firing frequencies and spike-rate-dependence plasticity (SRDP) dominates other regions. This demonstration provides a novel approach in neural coding implementation, which facilitates the development of bio-inspired computing systems.
License type:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Funding Info:
Description:
ISSN:
2045-2322
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