Gradient modelling of memristive systems
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Accesso online: | |
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| _version_ | 1866917985025785856 |
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| author | Forni, Fulvio Sepulchre, Rodolphe |
| author_facet | Forni, Fulvio Sepulchre, Rodolphe |
| contents | We introduce a gradient modeling framework for memristive systems. Our focus is on memristive systems as they appear in neurophysiology and neuromorphic systems. Revisiting the original definition of Chua, we regard memristive elements as gradient operators of quadratic functionals with respect to a metric determined by the memristance. We explore the consequences of gradient properties for the analysis and design of neuromorphic circuits. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_10093 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Gradient modelling of memristive systems Forni, Fulvio Sepulchre, Rodolphe Systems and Control Differential Geometry Dynamical Systems We introduce a gradient modeling framework for memristive systems. Our focus is on memristive systems as they appear in neurophysiology and neuromorphic systems. Revisiting the original definition of Chua, we regard memristive elements as gradient operators of quadratic functionals with respect to a metric determined by the memristance. We explore the consequences of gradient properties for the analysis and design of neuromorphic circuits. |
| title | Gradient modelling of memristive systems |
| topic | Systems and Control Differential Geometry Dynamical Systems |
| url | https://arxiv.org/abs/2504.10093 |