Abstract
An array of cross-point memristive devices has been implemented on the basis of yttria-stabilized zirconia thin film for applications in prototypes of spiking neural networks. The resistive switching phenomena and the plasticity nature of such memristive devices are studied. Reproducible bipolar resistive switching and precise tuning of resistive state are demonstrated and used to implement the plasticity rule according to STDP (spike-timing-dependent plasticity) mechanism. STDP learning is found to be dependent on the memristor's initial resistive state value and discussed in terms of the finite conductance change in studied structures. Obtained results provide the foundation for autonomous neuromorphic circuits with unsupervised learning development.
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