Results 41 to 50 of about 1,847,375 (374)

Experimental Validation of Machine Learning-Based Joint Failure Management and Quality of Transmission Estimation

open access: yesIEEE Photonics Journal, 2023
The exponentially growing demand for high-speed data necessitates more complex and versatile networks. Optimization and reliability assurance of such high-complexity networks is getting increasingly important.
Lars E. Kruse   +3 more
doaj   +1 more source

Ultra-High Resolution Wideband on-Chip Spectrometer

open access: yesIEEE Photonics Journal, 2020
Monitoring the state of the optical network is a key enabler for programmability of network functions, protocols and efficient use of the spectrum. A particular challenge is to provide the SDN-EON controller with a panoramic view of the complete state of
Mehedi Hasan   +6 more
doaj   +1 more source

Application of optical fiber transmission technology in coal mine monitoring system

open access: yesMeikuang Anquan, 2021
Aiming at the problems of short distance, slow speed, large loss and weak anti-electromagnetic interference ability of traditional cable in data transmission of coal mine monitoring system, this paper studies the optical fiber transmission technology and
LIU Fen
doaj   +1 more source

AI-Based Modeling and Monitoring Techniques for Future Intelligent Elastic Optical Networks

open access: yesApplied Sciences, 2020
With the development of 5G technology, high definition video and internet of things, the capacity demand for optical networks has been increasing dramatically. To fulfill the capacity demand, low-margin optical network is attracting attentions. Therefore,
Xiaomin Liu   +6 more
doaj   +1 more source

Optical Accelerometers for Detecting Low-Frequency Micro-Vibrations

open access: yesApplied Sciences, 2022
Optical accelerometers are high-precision inertial sensors that use optical measurement technology to achieve high-precision and electromagnetic interference-resistant acceleration measurements.
Ying-Jun Lei   +4 more
doaj   +1 more source

Transfer learning simplified multi-task deep neural network for PDM-64QAM optical performance monitoring.

open access: yesOptics Express, 2020
We experimentally demonstrate a transfer learning (TL) simplified multi-task deep neural network (MT-DNN) for joint optical signal-to-noise ratio (OSNR) monitoring and modulation format identification (MFI) from directly detected PDM-64QAM signals. First,
Yijun Cheng   +4 more
semanticscholar   +1 more source

Multi-Functional Optical Spectrum Analysis Using Multi-Task Cascaded Neural Networks

open access: yesIEEE Photonics Journal, 2022
In the optical communication systems, the optical spectrum (OS) provides useful informations for optical performance monitoring and optical link diagnosis.
Haoyu Wang   +5 more
doaj   +1 more source

Chromatic Dispersion, Nonlinear Parameter, and Modulation Format Monitoring Based on Godard's Error for Coherent Optical Transmission Systems

open access: yesIEEE Photonics Journal, 2018
This paper considers Godard's error as signal quality metric to monitor chromatic dispersion (CD), nonlinear parameter and modulation format in the DSP module of the coherent receivers.
Lin Jiang   +7 more
doaj   +1 more source

Machine Learning Applications for Short Reach Optical Communication

open access: yesPhotonics, 2022
With the rapid development of optical communication systems, more advanced techniques conventionally used in long-haul transmissions have gradually entered systems covering shorter distances below 100 km, where higher-speed connections are required in ...
Yapeng Xie   +3 more
doaj   +1 more source

Optical contamination screening of materials with a high-finesse Fabry-Perot cavity resonated continuously at 1.06-µm wavelength in vacuum [PDF]

open access: yes, 1999
An optical-loss measurement system based on a resonant Fabry Perot cavity at 1.06µm in vacuum has been developed for independent monitoring of the cavity total loss and the optical absorption loss.
Camp, Jordan, Coyne, Dennis, Li, Daqun
core   +1 more source

Home - About - Disclaimer - Privacy