IEEE Trans Neural Netw Learn Syst. 2015 Dec;26(12):3301-7. doi: 10.1109/TNNLS.2015.2404346. Epub 2015 Mar 3.
In this brief, we numerically demonstrate a photonic delay-based reservoir computing system, which processes, in parallel, two independent computational tasks even when the two tasks have unrelated input streams. Our approach is based on a single-longitudinal mode semiconductor ring laser (SRL) with optical feedback. The SRL emits in two directional optical modes. Each directional mode processes one individual task to mitigate possible crosstalk. We illustrate the feasibility of our scheme by analyzing the performance on two benchmark tasks: 1) chaotic time series prediction and 2) nonlinear channel equalization. We identify some feedback configurations for which the results for simultaneous prediction/classification indicate a good performance, but with slight degradation (as compared with the performance obtained for single task processing) due to nonlinear and linear interactions between the two directional modes of the laser. In these configurations, the system performs well on both tasks for a broad range of the parameters.
在本简介中,我们通过数值方法演示了一种基于光子延迟的储层计算系统,该系统可以并行处理两个独立的计算任务,即使这两个任务具有不相关的输入流。我们的方法基于具有光反馈的单纵模半导体环形激光器(SRL)。SRL 以两个定向光模式发射。每个定向模式处理一个单独的任务,以减轻可能的串扰。我们通过分析两个基准任务的性能来验证我们方案的可行性:1)混沌时间序列预测和 2)非线性信道均衡。我们确定了一些反馈配置,对于这些配置,同时进行预测/分类的结果表明性能良好,但由于激光的两个定向模式之间的非线性和线性相互作用,与单任务处理获得的性能相比略有下降。在这些配置中,系统在参数的广泛范围内对两个任务都能很好地执行。