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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Simultaneous Computation of Two Independent Tasks Using Reservoir Computing Based on a Single Photonic Nonlinear Node With Optical Feedback
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Simultaneous Computation of Two Independent Tasks Using Reservoir Computing Based on a Single Photonic Nonlinear Node With Optical Feedback

机译:基于带光反馈的单光子非线性节点的储层计算同时计算两个独立任务

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摘要

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.
机译:在此简介中,我们以数字方式演示了基于光子延迟的储层计算系统,即使两个任务具有无关的输入流,该系统也可以并行处理两个独立的计算任务。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发出两种定向光学模式。每种定向模式都处理一个单独的任务,以减轻可能的串扰。通过分析两个基准任务的性能,我们说明了该方案的可行性: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,对于这些反馈配置,同时进行预测/分类的结果显示出良好的性能,但是由于激光的两个定向模式之间的非线性和线性相互作用,其性能略有下降(与单任务处理获得的性能相比)。在这些配置中,系统在广泛的参数范围内都能很好地完成两项任务。

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