油藏计算
计算机科学
非线性系统
光子学
水准点(测量)
混乱的
计算
节点(物理)
电子工程
算法
光学
物理
人工智能
工程类
声学
人工神经网络
量子力学
循环神经网络
地理
大地测量学
作者
Romain Modeste Nguimdo,Guy Verschaffelt,Jan Danckaert,Guy Van der Sande
出处
期刊:IEEE transactions on neural networks and learning systems
[Institute of Electrical and Electronics Engineers]
日期:2015-12-01
卷期号:26 (12): 3301-3307
被引量:97
标识
DOI:10.1109/tnnls.2015.2404346
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.
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