Artificial neuron operations and spike-timing-dependent plasticity using memristive devices for brain-inspired computing. (9th March 2018)

• Record Type: Journal Article
• Authors: Marukame, Takao; Nishi, Yoshifumi; Yasuda, Shin-ichi; Tanamoto, Tetsufumi
• Is Part Of: Japanese journal of applied physics. Volume 57:Number 4(2018)Supplement
• Publication Date: 2018-03-09
• Subjects: Physics -- Periodicals; 621.05
• DOI: 10.7567/JJAP.57.04FK06
• Languages: English
• ISSNs: 0021-4922

Abstract

Abstract: The use of memristive devices for creating artificial neurons is promising for brain-inspired computing from the viewpoints of computation architecture and learning protocol. We present an energy-efficient multiplier accumulator based on a memristive array architecture incorporating both analog and digital circuitries. The analog circuitry is used to full advantage for neural networks, as demonstrated by the spike-timing-dependent plasticity (STDP) in fabricated AlO x /TiO x -based metal–oxide memristive devices. STDP protocols for controlling periodic analog resistance with long-range stability were experimentally verified using a variety of voltage amplitudes and spike timings.