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Cavalcade neural network for mobile robot

机译:移动机器人的行列神经网络

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摘要

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a robot.
机译:由于复杂的数学模型和缺乏直观的学习算法,尖峰神经网络的应用通常受到限制。在本文中,提出了一种从泄漏积分和发射神经元模型“行进”神经元派生而来的简单,新颖的神经网络。已经开发了神经网络的仿真,并在环境中实现了两种基本的学习算法。这些算法成功地学习了一些基本的时间和瞬时问题。然后从这些实验中获得对神经网络结构的启发,并将其应用于过程传感器信息,从而成功控制机器人。

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