标题： 光电储层计算 显示英文标题

标题： Optoelectronic Reservoir Computing

摘要： 储层计算是一种最近引入的高效生物启发方法，用于处理时间依赖的数据。 储层计算的基本方案包括一个非线性递归动力系统，该系统连接到一个输入层和一个输出层。 在这些限制条件下，有许多可能的实现方式。 在这里，我们报告了一种基于最近提出架构的光电储层计算实现，该架构包括一个非线性节点和一个延迟线。 我们的实现足够快，可用于实时信息处理。 我们展示了其在实际重要任务中的性能，例如非线性信道均衡和语音识别，并获得了与最先进的数字实现相当的结果。 显示英文摘要

摘要： Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a single output layer. Within these constraints many implementations are possible. Here we report an opto-electronic implementation of reservoir computing based on a recently proposed architecture consisting of a single non linear node and a delay line. Our implementation is sufficiently fast for real time information processing. We illustrate its performance on tasks of practical importance such as nonlinear channel equalization and speech recognition, and obtain results comparable to state of the art digital implementations.