Decision Making by a Neuromorphic Network of Volatile Resistive Switching Memories
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914670138359808 |
|---|---|
| author | Ricci, Saverio Kappel, David Tetzlaff, Christian Ielmini, Daniele Covi, Erika |
| author_facet | Ricci, Saverio Kappel, David Tetzlaff, Christian Ielmini, Daniele Covi, Erika |
| contents | The necessity of having an electronic device working in relevant biological time scales with a small footprint boosted the research of a new class of emerging memories. Ag-based volatile resistive switching memories (RRAMs) feature a spontaneous change of device conductance with a similarity to biological mechanisms. They rely on the formation and self-disruption of a metallic conductive filament through an oxide layer, with a retention time ranging from a few milliseconds to several seconds, greatly tunable according to the maximum current which is flowing through the device. Here we prove a neuromorphic system based on volatile-RRAMs able to mimic the principles of biological decision-making behavior and tackle the Two-Alternative Forced Choice problem, where a subject is asked to make a choice between two possible alternatives not relying on a precise knowledge of the problem, rather on noisy perceptions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2211_03081 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Decision Making by a Neuromorphic Network of Volatile Resistive Switching Memories Ricci, Saverio Kappel, David Tetzlaff, Christian Ielmini, Daniele Covi, Erika Emerging Technologies The necessity of having an electronic device working in relevant biological time scales with a small footprint boosted the research of a new class of emerging memories. Ag-based volatile resistive switching memories (RRAMs) feature a spontaneous change of device conductance with a similarity to biological mechanisms. They rely on the formation and self-disruption of a metallic conductive filament through an oxide layer, with a retention time ranging from a few milliseconds to several seconds, greatly tunable according to the maximum current which is flowing through the device. Here we prove a neuromorphic system based on volatile-RRAMs able to mimic the principles of biological decision-making behavior and tackle the Two-Alternative Forced Choice problem, where a subject is asked to make a choice between two possible alternatives not relying on a precise knowledge of the problem, rather on noisy perceptions. |
| title | Decision Making by a Neuromorphic Network of Volatile Resistive Switching Memories |
| topic | Emerging Technologies |
| url | https://arxiv.org/abs/2211.03081 |