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Updated: Jan 7, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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在使用尖端神经网络的动态系统中进行综合估计和控制的神经形态强大框架.

Reza Ahmadvand1, Sarah Safura Sharif1, Yaser Mike Banad2

  • 1School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, 73019, USA.

Scientific reports
|December 30, 2025
PubMed
概括

本研究介绍了一种新的,无学习的尖端神经网络 (SNN) 框架,用于机器人系统中的综合估计和控制. SNN-LQR-EMSIF提供了计算效率和稳定性,在动态系统挑战中表现优于传统方法.

关键词:
卡尔曼过器可以过.线性正方形高斯式神经形态计算是一种神经形态计算.卫星交会机动作 卫星交会机动滑动创新过器的创新过器尖的神经网络的神经网络.

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