Analog Sequential Hippocampal Memory Model for Trajectory Learning and Recalling: A Robustness Analysis Overview
The rapid expansion of information systems in all areas of society demands more powerful, efficient, and low‐energy consumption computing systems. Neuromorphic engineering has emerged as a solution that attempts to mimic the brain to incorporate its capabilities to solve complex problems in a comput...
Saved in:
| Main Authors: | Daniel Casanueva‐Morato, Alvaro Ayuso‐Martinez, Giacomo Indiveri, Juan P. Dominguez‐Morales, Gabriel Jimenez‐Moreno |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
|
| Series: | Advanced Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/aisy.202400282 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Analog Implementation of a Spiking System for Performing Arithmetic Logic Operations on Mixed‐Signal Neuromorphic Processors
by: Alvaro Ayuso‐Martinez, et al.
Published: (2025-04-01) -
A Realistic Simulation Framework for Analog/Digital Neuromorphic Architectures
by: Fernando M Quintana, et al.
Published: (2025-01-01) -
On the sampling sparsity of analog-to-spike conversion based on leaky integrate-and-fire
by: Bernhard A Moser, et al.
Published: (2025-01-01) -
Programmable Analog Circuits with Neuromorphic Nanostructured Platinum Films
by: Stefano Radice, et al.
Published: (2024-12-01) -
Understanding the functional roles of modelling components in spiking neural networks
by: Huifeng Yin, et al.
Published: (2024-01-01)