光子学
油藏计算
光子集成电路
计算机科学
小型化
光学计算
电子工程
节点(物理)
光学
物理
电气工程
人工智能
人工神经网络
工程类
循环神经网络
量子力学
作者
Kiminori Takano,Chihiro Sugano,Masanobu Inubushi,Kazuyuki Yoshimura,Satoshi Sunada,Kazutaka Kanno,Atsushi Uchida
出处
期刊:Optics Express
[The Optical Society]
日期:2018-10-26
卷期号:26 (22): 29424-29424
被引量:91
摘要
Photonic reservoir computing is a new paradigm for performing high-speed prediction and classification tasks in an efficient manner. The major challenge for the miniaturization of photonic reservoir computing is the need for the use of photonic integrated circuits. Herein, we experimentally demonstrate reservoir computing using a photonic integrated circuit with a semiconductor laser and a short external cavity. We propose a method to increase the number of virtual nodes in delayed feedback using short node intervals and outputs from multiple delay times. We perform time-series prediction and nonlinear channel equalization tasks using reservoir computing with the photonic integrated circuit. We show that the photonic integrated circuit with optical feedback outperforms the photonic integrated circuit without optical feedback for prediction tasks. To enhance the memory effect we feed past input signals in the current input data and demonstrate successful performance in an n-step-ahead prediction task.
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