Results 21 to 30 of about 8,453,335 (366)
Maximizing the optical network capacity [PDF]
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2016 Most of the digital data transmitted are carried by optical fibres, forming the great part of the national and international communication infrastructure. The information-carrying capacity of these networks has increased vastly over the past decades through the introduction of wavelength division multiplexing, advanced modulation formats, digital ...
Polina Bayvel +7 more
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IEEE Photonics Journal, 2021 Increasing the threshold of stimulated Brillouin scattering (SBS) by frequency and phase modulation is a productive approach to suppress SBS in optical fiber communications.
Peng Lei +6 more
doaj +1 more source
IEEE Photonics Journal, 2022 We implement a compact optical frequency standard at the wavelength of 852 nm by the modulation transfer spectroscopy (MTS) technique, using a Faraday laser as the local oscillator and a double-layer cesium vapor cell to provide frequency reference.
Hangbo Shi +5 more
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The Optical RL-Gym: An open-source toolkit for applying reinforcement learning in optical networks
International Conference on Transparent Optical Networks, 2020 Reinforcement Learning (RL) is leading to important breakthroughs in several areas (e.g., self-driving vehicles, robotics, and network automation). Part of its success is due to the existence of toolkits (e.g., OpenAI Gym) to implement standard RL tasks.
Carlos Natalino, P. Monti
semanticscholar +1 more source
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation [PDF]
Computer Vision and Pattern Recognition, 2015 Recent work has shown that optical flow estimation can be formulated as a supervised learning task and can be successfully solved with convolutional networks. Training of the so-called FlowNet was enabled by a large synthetically generated dataset.
N. Mayer +6 more
semanticscholar +1 more source
Multilayer Optical Learning Networks [PDF]
Topical Meeting on Optical Computing, 1987 In this paper we present a new approach to multilayer neural network learning which is based on holographically interconnected nonlinear Fabry-Perot etalons. The network can learn the interconnections that form a distributed representation of a desired pattern transformation operation.
Wagner, Kelvin, Psaltis, Demetri
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Generation of the First-Order OAM Modes in Ring Fibers by Exerting Pressure Technology
IEEE Photonics Journal, 2017 We have proposed an effective method of generating the first-order orbital angular momentum (OAM) modes in ring fibers. The first-order OAM modes (L = ±1) can be represented as the linear superposition of the HE21even mode and the HE21odd mode ...
Yu Zhang +9 more
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MDM-TDM PON Utilizing Self-Coherent Detection-Based OLT and RSOA-Based ONU for High Power Budget
IEEE Photonics Journal, 2016 A cost-effective mode-division-multiplexing and time-division-multiplexing passive optical network (MDM-TDM PON) utilizing a self-coherent detection for upstream signal at optical line terminal (OLT) and a high-gain reflective semiconductor optical ...
Yuanxiang Chen +11 more
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High Bandwidth Utilization DWBA Algorithm for Upstream Channel in NG-EPON
IEEE Access, 2022 In this paper, an (ONU-load and RTTs)-based (OLR) dynamic wavelength and bandwidth allocation (DWBA) algorithm for upstream channel in next-generational Ethernet passive optical network (NG-EPON) is proposed.
Jianqiang Hui +3 more
doaj +1 more source
Optical Axons for Electro-Optical Neural Networks [PDF]
Sensors, 2020 Recently, neuromorphic sensors, which convert analogue signals to spiking frequencies, have been reported for neurorobotics. In bio-inspired systems these sensors are connected to the main neural unit to perform post-processing of the sensor data. The performance of spiking neural networks has been improved using optical synapses, which offer parallel ...
Mircea Hulea +4 more
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