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Formal Aspects of Streaming Recurrent Neural Networks

机译:流式递归神经网络的形式方面

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Streaming recurrent neural networks with linear and spiral space-time structures are analyzed. Formal aspects of the construction and operation of such networks are considered. Four types of synapses are identified in such networks. One of them is the track synapses, which ensure the advancement of signals over the network. Three other types are synapses of dynamic memory. Additionally to traditional synapse weights the attenuation functions of diverging and converging signals are taken into account. The results of simulation of signal processing by streaming recurrent networks with different structures of their layers are presented.
机译:分析了具有线性和螺旋时空结构的流式递归神经网络。考虑了此类网络的构建和运行的形式方面。在这样的网络中识别出四种类型的突触。轨道突触就是其中之一,它可以确保网络上信号的传输。其他三种类型是动态内存的突触。除传统突触权重外,还考虑了发散和会聚信号的衰减功能。给出了通过分层结构不同的流式递归网络对信号处理进行仿真的结果。

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