This paper presents a method for reproducing a simple central pattern generator (CPG) using a modified Echo State Network (ESN). Conventionally, the dynamical reservoir needs to be damped to stabilize and preserve memory. However, we find that a reservoir that develops oscillatory activity without any external excitation can mimic the behaviour of a simple CPG in biological systems. We define the specific neuron ensemble required for generating oscillations in the reservoir and demonstrate how adjustments to the leaking rate, spectral radius, topology, and population size can increase the probability of reproducing these oscillations. The results of the experiments, conducted on the time series simulation tasks, demonstrate that the ESN is able to generate the desired waveform without any input. This approach offers a promising solution for the development of bio-inspired controllers for robotic systems.

翻译：本文提出了一种利用改进的回声状态网络（Echo State Network, ESN）重现简单中枢模式发生器（Central Pattern Generator, CPG）的方法。传统上，动力储层需要被阻尼以稳定并保持记忆。然而，我们发现，无需任何外部激励即可发展出振荡活动的储层能够模拟生物系统中简单CPG的行为。我们定义了在储层中生成振荡所需的特定神经元集合，并展示了如何调整泄漏率、谱半径、拓扑结构和种群大小来提高重现这些振荡的概率。在时间序列仿真任务上进行的实验结果表明，ESN能够在无任何输入的情况下生成所需波形。该方法为开发用于机器人系统的生物启发式控制器提供了一种有前景的解决方案。