Reservoir computing (RC) offers efficient temporal data processing with a low training cost by separating recurrent neural networks into a fixed network with recurrent connections and a trainable linear network. The quality of the fixed network, called reservoir, is the most important factor that determines the performance of the RC system. In this paper, we investigate the influence of the hierarchical reservoir structure on the properties of the reservoir and the performance of the RC system. Analogous to deep neural networks, stacking sub-reservoirs in series is an efficient way to enhance the nonlinearity of data transformation to high-dimensional space and expand the diversity of temporal information captured by the reservoir. These deep reservoir systems offer better performance when compared to simply increasing the size of the reservoir or the number of sub-reservoirs. Low frequency components are mainly captured by the sub-reservoirs in later stage of the deep reservoir structure, similar to observations that more abstract information can be extracted by layers in the late stage of deep neural networks. When the total size of the reservoir is fixed, tradeoff between the number of sub-reservoirs and the size of each sub-reservoir needs to be carefully considered, due to the degraded ability of individual sub-reservoirs at small sizes. Improved performance of the deep reservoir structure alleviates the difficulty of implementing the RC system on hardware systems.

中文翻译：

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储层计算系统中的分层体系结构

储层计算（RC）通过将递归神经网络分离为具有递归连接和可训练线性网络的固定网络，以较低的培训成本提供了有效的时间数据处理。称为水库的固定网络的质量是决定RC系统性能的最重要因素。在本文中，我们研究了分层储层结构对储层性质和RC系统性能的影响。类似于深层神经网络，串联堆叠子储层是一种有效的方法，可以增强将数据转换为高维空间的非线性并扩展由储层捕获的时间信息的多样性。与仅增加水库的大小或子水库的数量相比，这些深水库系统提供了更好的性能。低频分量主要由深层储层结构后期的子储层捕获，类似于在深层神经网络的后期可以通过层提取更多抽象信息的观察。当储层的总大小固定时，由于小规模的单个子储层的性能下降，需要仔细考虑子储层的数量与每个子储层的大小之间的折衷。深层储层结构的改进性能减轻了在硬件系统上实施RC系统的难度。低频分量主要由深层储层结构后期的子储层捕获，类似于在深层神经网络的后期可以通过层提取更多抽象信息的观察。当储层的总大小固定时，由于小规模的单个子储层的性能下降，需要仔细考虑子储层的数量与每个子储层的大小之间的折衷。深层储层结构的改进性能减轻了在硬件系统上实施RC系统的难度。低频分量主要由深层储层结构后期的子储层捕获，类似于在深层神经网络的后期可以通过层提取更多抽象信息的观察。当储层的总大小固定时，由于小规模的单个子储层的性能下降，需要仔细考虑子储层的数量与每个子储层的大小之间的折衷。深层储层结构的改进性能减轻了在硬件系统上实施RC系统的难度。由于小尺寸的单个子水库的性能下降，因此需要仔细考虑子水库的数量与每个子水库的大小之间的折衷。深层储层结构的改进性能减轻了在硬件系统上实施RC系统的难度。由于小尺寸的单个子水库的性能下降，因此需要仔细考虑子水库的数量与每个子水库的大小之间的折衷。深层储层结构的改进性能减轻了在硬件系统上实施RC系统的难度。