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A PROPOSAL OF NEURON MODEL CAPABLE OF NEURITE ELONGATION BY NGF BASED ON PHYSIOLOGICAL CHARACTERISTICS

机译:基于生理特性的NGF能够通过NGF的神经元模型的提议

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This paper proposes a physiologic mathematical model for a minimal neural network. Then, the mathematical models of neurocyte may automatically form small-neural networks if being able to use self-organization algorithm in the future. The results in this paper indicate that this simulation model was able to simulate "NGF taxis of axon" known as one of characteristics of the neurocyte. This "taxis" is one of the significant functions for control of self-organization. In particular, this mathematical model includes potentiality that is able to design the small-neural networks that can mimic functions of insect's simple-nervous systems autonomously. There is an expectation that the results can be applied to the improvement of the self-growth miniature robot's controller in the future. However, this mathematical model has limitations in that the computing time to look for a network that satisfies the necessary conditions increases when a more complex neural network is required.
机译:本文提出了一种最小神经网络的生理学数学模型。然后,如果能够在将来使用自组织算法,神经细胞的数学模型可以自动形成小神经网络。本文的结果表明,该仿真模型能够模拟称为神经细胞特征之一的“轴突的NGF出租车”。这个“出租车”是控制自我组织的重要功能之一。特别地,该数学模型包括能够设计可以自主地模仿昆虫简单神经系统的小神经网络的潜力。期望在未来的自我增长微型机器人控制器的改善方面可以应用结果。然而,该数学模型具有限制,因为当需要更复杂的神经网络时,要查找满足必要条件的网络的计算时间。

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