A single Si:HfO2-based device can be programmed as either a multi-level memcapacitor or a memristor, and simulations show using both modes improves recurrent spiking network accuracy on the SHD task.
Unified Memcapacitor-Memristor Memory for Synaptic Weights and Neuron Temporal Dynamics
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abstract
We present a fabricated and experimentally characterized memory stack that unifies memristive and memcapacitive behavior. Exploiting this dual functionality, we design a circuit enabling simultaneous control of spatial and temporal dynamics in recurrent spiking neural networks (RSNNs). Hardware-aware simulations highlight its promise for efficient neuromorphic processing.
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Unified Memcapacitor-Memristor Memory for Synaptic Weights and Neuron Temporal Dynamics
A single Si:HfO2-based device can be programmed as either a multi-level memcapacitor or a memristor, and simulations show using both modes improves recurrent spiking network accuracy on the SHD task.