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J Li, Z Li, F Chen, A Bicchi, Y Sun… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Neuro-robotics systems (NRSs) is the current state-of-the-art research with the strategic
alliance of neuroscience and robotics. It endows the next generation of robots with …

In the realm of hybrid brain: Human brain and AI

H Fares, M Ronchini, M Zamani, H Farkhani… - arxiv preprint arxiv …, 2022 - arxiv.org
With the recent developments in neuroscience and engineering, it is now possible to record
brain signals and decode them. Also, a growing number of stimulation methods have …

Hybrid CMOS-Memristor synapse circuits for implementing Ca ion-based plasticity model

JG Lim, S Park, SM Lee, Y Jeong, J Kim, S Lee… - Scientific reports, 2024 - nature.com
Neuromorphic computing research is being actively pursued to address the challenges
posed by the need for energy-efficient processing of big data. One of the promising …

Supervised Learning Algorithm for Multilayer Spiking Neural Networks with Long‐Term Memory Spike Response Model

X Lin, M Zhang, X Wang - Computational Intelligence and …, 2021 - Wiley Online Library
As a new brain‐inspired computational model of artificial neural networks, spiking neural
networks transmit and process information via precisely timed spike trains. Constructing …

Pulsewidth modulation-based algorithm for spike phase encoding and decoding of time-dependent analog data

A Arriandiaga, E Portillo… - … on Neural Networks …, 2019 - ieeexplore.ieee.org
This article proposes a new spike encoding and decoding algorithm for analog data. The
algorithm uses the pulsewidth modulation principles to achieve a high reconstruction …

Optimizing information processing in brain-inspired neural networks

B Paprocki, A Pregowska… - Bulletin of the Polish …, 2020 - yadda.icm.edu.pl
The way brain networks maintain high transmission efficiency is believed to be fundamental
in understanding brain activity. Brains consisting of more cells render information …