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/AlO x /TaO x /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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Sun et al. (2018) studied this question.
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