US Naval Research Lab, Washington, DC 20375, USA.
Chaos. 2020 Jan;30(1):013102. doi: 10.1063/1.5128898.
A reservoir computer is a complex dynamical system, often created by coupling nonlinear nodes in a network. The nodes are all driven by a common driving signal. In this work, three dimension estimation methods, false nearest neighbor, covariance dimension, and Kaplan-Yorke dimension, are used to estimate the dimension of the reservoir dynamical system. It is shown that the signals in the reservoir system exist on a relatively low dimensional surface. Changing the spectral radius of the reservoir network can increase the fractal dimension of the reservoir signals, leading to an increase in a testing error.
储层计算机是一种复杂的动力系统，通常通过在网络中耦合非线性节点来创建。这些节点都由一个共同的驱动信号驱动。在这项工作中，使用了三维估计方法，即伪最近邻法、协方差维数法和卡普兰-约克维数法，来估计储层动力系统的维数。结果表明，储层系统中的信号存在于一个相对较低的维表面上。改变储层网络的谱半径可以增加储层信号的分形维数，从而导致测试误差的增加。
