Arbitrary Spike Time Dependent Plasticity (STDP) in memristor by analog waveform engineering
Document Type
Article
Publication Date
6-1-2017
Abstract
In the literature, various pulse-based programming schemes have been used to mimic typical spike time-dependent plasticity (STDP)-based learning rule observed in biological synapses. In this letter, we demonstrate the capability to generated arbitrary STDP behaviors by using analog programming waveforms inspired by neuronal action potential. First, we propose a simple algorithm to generate any arbitrary form of STDP. Second, we show the feasibility of a range of spike correlation time scales for STDP, e.g., biological ( ∼100 ms) to accelerated (∼20μs), based on W/ r0.7Ca0.3MnO3/Pt based memristor. Third, we experimentally demonstrate several forms of STDP behaviors, where the pre- and post-neuronal waveforms are randomly spaced in time, akin to operational conditions. STDP shape corresponds well to waveforms. Thus, we show that artificial synapses can achieve the richness observed in biology as well as a range of STDP timescales for biologically compatible to accelerated neural network applications.
Identifier
85021770026 (Scopus)
Publication Title
IEEE Electron Device Letters
External Full Text Location
https://doi.org/10.1109/LED.2017.2696023
ISSN
07413106
First Page
740
Last Page
743
Issue
6
Volume
38
Fund Ref
Department of Science and Technology, Ministry of Science and Technology, India
Recommended Citation
Panwar, Neeraj; Rajendran, Bipin; and Ganguly, Udayan, "Arbitrary Spike Time Dependent Plasticity (STDP) in memristor by analog waveform engineering" (2017). Faculty Publications. 9547.
https://digitalcommons.njit.edu/fac_pubs/9547
