Firing Patterns and Synchronicity of Locally Active Memristor-Based Neuromorphic Circuits
Neuromorphic circuits with diverse neuronal firing features are the foundation for implementing neuron-based intelligent tasks. The locally active memristor (LAM) is a good candidate for constructing such kind of artificial circuits. However, it is attractive and challenging to explore synchronicity of firing patterns between LAM-based neuromorphic circuits, especially on hardware level. To this end, a neuromorphic circuit is constructed with a newly designed LAM emulator, a capacitor, a DC voltage, and an external current stimulus. Abundant stimulus-relating firing patterns are numerically revealed, whose bifurcation mechanism are theoretically discussed. Besides, using a LAM emulator as the coupling synapse, the interactions between two firing neuromorphic circuits are explored under identical and nonidentical stimulus conditions. The results manifest that the amplitude and phase of the stimulus current, as well as the static potential of the LAM branch, all exert significant influences on the synchronization behaviors. Furthermore, PCB-based analog circuits are implemented to demonstrate the firing patterns of single and coupled neuromorphic circuits from the perspective of physical experiments. This research could provide a viable paradigm to theoretical research and engineering application of memristive neuromorphic circuits.
Authors
- Quan Xu (ORCID: https://orcid.org/0000-0002-0370-9141)
- Huagan Wu (ORCID: https://orcid.org/0000-0001-9480-033X)
- Yuchen Zhang (ORCID: https://orcid.org/0009-0007-7476-6008)
- Mo Chen (ORCID: https://orcid.org/0000-0003-1841-7608)
Institutions
- Changzhou University (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits and Systems I Regular Papers
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1109/tcsi.2025.3564662
- Citations
- 3
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.19
Funders
- National Natural Science Foundation of China