We present an experimental validation of a recently proposed optimization technique for reservoir computing, using an optoelectronic setup. Reservoir computing is a robust framework for signal processing applications, and the development of efficient optimization approaches remains a key challenge. The technique we address leverages solely a delayed version of the input signal to identify the optimal operational region of the reservoir, simplifying the traditionally time-consuming task of hyperparameter tuning. We verify the effectiveness of this approach on different benchmark tasks and reservoir operating conditions.

翻译：我们提出了一种针对储层计算近期优化技术的实验验证，采用光电装置作为实现平台。储层计算是信号处理应用的稳健框架，而开发高效的优化方法仍是一项关键挑战。我们所关注的技术仅利用输入信号的延迟版本即可识别储层的最佳工作区域，这简化了传统上耗时的超参数调优过程。我们通过不同基准任务和储层运行条件验证了该方法的有效性。