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XOR learning by spiking neural network with infrared communications

机译：通过使用红外通信增强神经网络来进行XOR学习

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A Spiking Neural Network (SNN), which expresses information by spike trains, has an ability to process information with low energy like a human brain. Hardware implementation of a SNN is an important research problem. If the neurons are linked by wireless communications, SNNs can obtain the spatial degree of freedom, which may extend application area dramatically. Additionally, such SNNs can process information with low energy, owing to wireless communication by the spike trains. Therefore, it is regarded as low power-consumption wireless sensor networks (WSNs) with adding the functions of SNN neurons to wireless sensor nodes. This “Wireless Neural Sensor Networks” can distribute information processing like a brain on the WSN nodes. This paper presents a SNN with infrared(IR) communications as the first step of the above concept. Neurons are implemented by field programmable gate array, which are linked by IR communications. The implemented SNN succeeded in acquiring the XOR function through reinforcement learning.
机译：尖峰神经网络（SNN）通过尖峰火车表达信息，具有像人脑一样以低能量处理信息的能力。 SNN的硬件实现是一个重要的研究问题。如果神经元通过无线通信链接，则SNN可以获得空间自由度，这可能会极大地扩展应用范围。另外，由于尖峰列车的无线通信，这种SNN可以以低能量处理信息。因此，它被认为是低功耗无线传感器网络（WSN），它在无线传感器节点上增加了SNN神经元的功能。这种“无线神经传感器网络”可以在WSN节点上像大脑一样分布信息处理。本文提出了具有红外（IR）通信的SNN，作为上述概念的第一步。神经元由现场可编程门阵列实现，该阵列通过红外通信链接。实施的SNN通过强化学习成功获得了XOR功能。

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