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Updated: Jun 6, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

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在一个随机连接的神经网络中,对激活和学习值的步骤控制同步,朝着硬件实现的硬件实现

Kumiko Nomura1, Yoshifumi Nishi1

  • 1Frontier Research Laboratory, Corporate Research and Development Center, Toshiba Corporation, Kawasaki, Japan.

Frontiers in neuroscience
|November 28, 2024
PubMed
概括

本研究介绍了自组织机制,内在可塑性 (IP) 和突触可塑性 (SP),用于尖端神经网络 (SNN) 来改善时间数据处理. 拟议的模型提高了SNN在异常检测等任务中的性能,实现了完美的准确性.

关键词:
这是一种内在的可塑性.这是一个神经形态芯片.随机连接的神经网络是随机连接的神经网络.尖的神经网络的神经网络.突触性可塑性 突触性可塑性

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