Noise-induced homeostasis in memristor-based neuromorphic systems
In this work, it is experimentally demonstrated that noise can be used to emulate the biological homeostatic neuron property in memristor-based neuromorphic systems. The addition of an external noise to the bias allows regulating the memristor performance when used as an artificial neuron, controlli...
| Autores: | , , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:299290 |
| Acceso en línea: | https://ddd.uab.cat/record/299290 https://dx.doi.org/urn:doi:10.1109/LED.2024.3416704 |
| Access Level: | acceso abierto |
| Palabra clave: | Memristor RRAM Resistive switching Stochastic resonance Homeostasis Spike neural networks SPICE |
| Sumario: | In this work, it is experimentally demonstrated that noise can be used to emulate the biological homeostatic neuron property in memristor-based neuromorphic systems. The addition of an external noise to the bias allows regulating the memristor performance when used as an artificial neuron, controlling the firing process through the modulation of the memristor threshold voltages. Experimental results have been correctly addressed using the Dynamic Memdiode Model (DMM) for memristors in the framework of SPICE simulation. |
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