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Retina shows an extremely high signal processing efficiency because of its specific signal processing strategy which called computing in sensor. In retina, photoreceptor cells encode light signals into spikes and ganglion cells finish the shape perception process. In order to realize the neuromorphic vision sensor, the one-transistor-one-memristor (1T1M) structure which formed by one memristor and one MOSFET in serial is used to construct photoreceptor cell and ganglion cell. The voltage changes between two terminals of memristor and MOSFET can mimic the changes of membrane potential caused by spikes and illumination respectively. In this paper, the tunable memristive neurons with 1T1M structures are built. According to the concept of receptive field of ganglion cells (GCs) in the retina, the artificial shape perception retina network is constructed with these memristive neurons. The final results show that the artificial retina can extract shape information from the image and transfer it into spike frequency realizing the function of computing in sensor.

For the first time, this work investigated the timedependent variability (TDV) in RRAMs and its interaction with the RRAM-based analog neuromorphic circuits for pattern recognition. It is found that even the circuits are well trained, the TDV effect can introduce non-negligible recognition accuracy drop during the operating condition. The impact of TDV on the neuromorphic circuits increases when higher resistances are used for the circuit implementation, challenging for the future low power operation. In addition, the impact of TDV cannot be suppressed by either scaling up with more synapses or increasing the response time and thus threatens both real-time and general-purpose applications with high accuracy requirements. Further study on different circuit configurations, operating conditions and training algorithms, provides guidelines for the practical hardware implementation.

In this letter, new endurance degradation behaviors in the bipolar resistive random access memory devices with multilayered HfOx/TiOx are reported for the first time, showing almost a constant resistance in low resistance state and a gradually reduced resistance in high resistance state (HRS). Further investigations into the dependence of HRSs degradation speed on switching voltage and temperature reveal that the degradation is attributed to the oxygen ion (O 2− ) loss effect during RESET process, which leads to the insufficient O 2− supply for recombining the oxygen vacancies. Possible technical solutions are then proposed to improve the endurance performance.Index Terms-Endurance, oxygen ion, oxygen vacancy, reliability, resistive random access memory (RRAM), resistive switching.

A resistive switching device with inherent nonlinear characteristics through a delicately engineered interfacial layer is an ideal component to be integrated into passive crossbar arrays for the suppression of sneaking current, especially in ultra-dense 3D integration. In this paper, we demonstrated a TaO-based bipolar resistive switching device with a nearly symmetrical bi-directional nonlinear feature through interface engineering. This was accomplished by introducing an ultra-thin interfacial layer (SiO) with unique features, including a large band gap and a certain level of negative heat of oxide formation between the top electrode (TiN) and resistive layer (TaO). The devices exhibit excellent nonlinear property under both positive and negative bias. Modulation of the inherent nonlinearity as well as the resistive switching mechanism are comprehensively studied by scrutinizing the results of the experimental control groups and the extensive characterizations including detailed compositional analysis, which suggests that the underlying mechanism of the nonlinear behavior is associatively governed by the serially connected metallic conductive filament and Flower-Nordheim tunneling barrier formed by the SiO interface layer. The proposed device in this work has great potential to be implemented in future massive storage memory applications of high-density selector-free crossbar structure.