Emerging brain-inspired neuromorphic computing paradigms require devices that can emulate the complete functionality of biological synapses upon different neuronal activities in order to process big data flows in an efficient and cognitive manner while being robust against any noisy input. The memristive device has been proposed as a promising candidate for emulating artificial synapses due to their complex multilevel and dynamical plastic behaviors. In this work, we exploit ultrastable analog BiFeO3 (BFO)-based memristive devices for experimentally demonstrating that BFO artificial synapses support various long-term plastic functions, i.e., spike timing-dependent plasticity (STDP), cycle number-dependent plasticity (CNDP), and spiking rate-dependent plasticity (SRDP). The study on the impact of electrical stimuli in terms of pulse width and amplitude on STDP behaviors shows that their learning windows possess a wide range of timescale configurability, which can be a function of applied waveform. Moreover, beyond SRDP, the systematical and comparative study on generalized frequency-dependent plasticity (FDP) is carried out, which reveals for the first time that the ratio modulation between pulse width and pulse interval time within one spike cycle can result in both synaptic potentiation and depression effect within the same firing frequency. The impact of intrinsic neuronal noise on the STDP function of a single BFO artificial synapse can be neglected because thermal noise is two orders of magnitude smaller than the writing voltage and because the cycle-to-cycle variation of the current–voltage characteristics of a single BFO artificial synapses is small. However, extrinsic voltage fluctuations, e.g., in neural networks, cause a noisy input into the artificial synapses of the neural network. Here, the impact of extrinsic neuronal noise on the STDP function of a single BFO artificial synapse is analyzed in order to understand the robustness of plastic behavior in memristive artificial synapses against extrinsic noisy input.
The high demand for performance and energy efficiency poses significant challenges for computing systems in recent years. The memristor-based crossbar array architecture is enthusiastically regarded as a potential competitor to traditional solutions due to its low power consumption and fast switching speed. Especially by leveraging self-rectifying memristive devices, passive crossbar arrays potentially enable high memory densities. Nonetheless, due to the lack of a switching control per cell, these passive, self-rectifying memristive crossbar arrays (srMCA) suffer from sneak path current issues that limit the range of accurate operation of the crossbar array. In this work, the sneak path current issues in the passive srMCAs based on self-rectifying bipolar and complementary switching memristive devices are comparatively analyzed. Under consideration of the worst-case scenario, three reading schemes are investigated: one wordline pull-up (OneWLPU), all wordline pull-up (AllWLPU), and floating (FL) reading schemes. As a conclusion, despite different switching dynamics, both types of self-rectifying memristive devices can efficiently suppress sneak path current in the srMCAs. In the FL reading scheme, the sneak path current flowing through the unselected reversely biased memristive cells in the srMCA can be considered as an accurate estimation for the practical sneak path current in the srMCA. By analyzing the sneak path current in the srMCAs with a size up to 64 × 64, it is demonstrated that the leakage current plays a crucial role for suppressing the sneak path current, and the sneak path current via an individual cell exhibits a continuous decrease while the accumulated total sneak path current in the unselected reverse biased region is increasing with expanding the crossbar size. The comparative study on the bipolar and complementary memristive devices based srMCAs under diverse reading schemes reveals the influence of the switching dynamics on the sneak path current effect in the srMCAs, and provides a beneficial reference and feasible solutions for the future optimization of the crossbar topology with the intention of mitigating sneak path effects.
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