Unified Memcapacitor-Memristor Memory for Synaptic Weights and Neuron Temporal Dynamics
Simone D'Agostino, Marco Massarotto, Tristan Torchet, Filippo Moro, Niccol\`o Castellani, Laurent Grenouillet, Yann Beilliard, David Esseni, Melika Payvand, Elisa Vianello

TL;DR
This paper introduces a novel memory device combining memristive and memcapacitive properties, enabling advanced control of neural network dynamics for more efficient neuromorphic computing.
Contribution
The work presents a fabricated memory stack with dual memristive and memcapacitive behavior, and a circuit design for improved neural network control.
Findings
Hardware-aware simulations show promising neuromorphic processing capabilities.
Experimental characterization confirms dual memristive-memcapacitive functionality.
The memory device enables simultaneous control of spatial and temporal neural dynamics.
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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Taxonomy
TopicsAdvanced Memory and Neural Computing · Neural Networks and Reservoir Computing · Ferroelectric and Negative Capacitance Devices
