Journal
IEEE ELECTRON DEVICE LETTERS
Volume 39, Issue 9, Pages 1298-1301Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LED.2018.2860053
Keywords
Neuromorphic computing; memristor; analog synapse; long-term retention
Categories
Funding
- National Natural Science Foundation of China [61604177, 61471377, 61704191]
- National University of Defense Technology [JC15-04-02]
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Electronic synapse with precise analog weight tuning ability and long-term retention is the vital device foundation of memristor-based neuromorphic computing systems. In this letter, we propose a Ti/AlOX/TaOX/Pt memristor as an analog synapse for memristive neural network applications. The device shows high uniformity, excellent analog switching behaviors (up to 200 resistance states under triangle pulses) and excellent long-term retention of each state (up to 30 000 s). Furthermore, the precise modulation of the device resistance state (with 1.7% tolerance) can also be achieved by a finer writing program within 50 cycles.
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