人工神经网络的最新进展及其在火星机器人中的应用

R. Hong
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引用次数: 0

摘要

这是对人工神经网络(ANN)的最新技术以及神经控制在火星机器人上的应用的广泛研究。重点是实现聚合所需的迭代次数的最小化,以及更具有生物动机的范例。涵盖的三个主要观点是任何种类或技术的神经网络实现的发展,新的神经网络理论和范式的发展,以及神经网络的实际,市场应用的发展及其在市场上的影响,甚至神经科学技术进步的影响,高Tc超导的实现,与人工智能的混合方法,都被涵盖。除了在空间机器人应用方面的好处外,人工神经网络在解决国家航空航天飞机的一些具有挑战性的问题方面具有相当大的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State-of-the-Art Of Artificial Neural Networks And Applications To Mars Robots
This is a broad examination of the state-of-the-art of artificial neural networks (ANN) and with applications of neurocontrol to Mars Robots. The emphasis is on the minimization of the number of iterations required to achieve convergence and the more biologically motivated paradigms. The three major perspectives covered are the development of neural network implementations of any variety or technology, the development of new neural network theory and paradigms and the development of practical, marketable applications of neural networks and their influence in the marketplace, Even the impact of technical advances in neuroscience, implementation with high Tc superconductivity, a hybrid approach with artificial intelligence, is covered. Besides benefits in its applications to space robots, artificial neural networks hold considerable promise of solving some of the challenging problems for the National Aerospace Plane.
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