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.
@article{arxiv.2506.22227,
title = {Unified Memcapacitor-Memristor Memory for Synaptic Weights and Neuron Temporal Dynamics},
author = {Simone D'Agostino and Marco Massarotto and Tristan Torchet and Filippo Moro and Niccolò Castellani and Laurent Grenouillet and Yann Beilliard and David Esseni and Melika Payvand and Elisa Vianello},
journal= {arXiv preprint arXiv:2506.22227},
year = {2025}
}
Comments
2 pages, accepted and discussed at Silicon Nanoelectronics Workshop 2025