Generalized synchronization between coupled dynamical systems is a phenomenon
of relevance in applications that range from secure communications to
physiological modelling. Here we test the capabilities of reservoir computing
and, in particular, echo state networks for the detection of generalized
synchronization. A nonlinear dynamical system consisting of two coupled
R\"ossler chaotic attractors is used to generate temporal series consisting of
time-locked generalized synchronized sequences interleaved by unsynchronized
ones. Correctly tuned, echo state networks are able to efficiently discriminate
between unsynchronized and synchronized sequences. Compared to other
state-of-the-art techniques of synchronization detection, the online
capabilities of the proposed ESN based methodology make it a promising choice
for real-time applications aiming to monitor dynamical synchronization changes
in continuous signals.

研究测试了储层计算和普遍同步检测，通过 Rössler 混沌吸引子实现时间序列中的同步和非同步序列的区分，并证明了基于 ESN 的同步检测方法具有在线检测能力，对于监测连续信号的动力学同步变化具有很好的应用前景。