Results 71 to 80 of about 263,497 (176)

Enhancement of Extreme Learning Machine for Estimating Blocking Probability of OCS Networks With Fixed-Alternate Routing

IEEE Access, 2019
In previous work, we proposed a neural network approach to estimate the blocking probability of optical networks with fixed routing. The neural network was implemented by the extreme learning machine (ELM) framework, in which the training inputs were the
Shuo Li, Ho Chun Leung, Eric Wing Ming Wong, Chi Sing Leung   +3 more
doaj   +1 more source

Flexible orbital angular momentum mode switching in multimode fibre using an optical neural network chip

Light: Advanced Manufacturing
Mode-division multiplexing technology has been proposed as a crucial technique for enhancing communication capacity and alleviating growing communication demands.
Zhengsen Ruan, Yuanjian Wan, Lulu Wang, Wei Zhou, Jian Wang   +4 more
doaj   +1 more source

Optical frontend for a convolutional neural network

Applied Optics, 2019
The parallelism of optics and the miniaturization of optical components using nanophotonic structures, such as metasurfaces present a compelling alternative to electronic implementations of convolutional neural networks. The lack of a low-power optical nonlinearity, however, requires slow and energy-inefficient conversions between the electronic and ...
Shane Colburn, Yi Chu, Eli Shilzerman, Arka Majumdar   +3 more
openaire   +3 more sources

A Neural Network Computational Spectrometer Trained by a Small Dataset with High-Correlation Optical Filters

Sensors
A computational spectrometer is a novel form of spectrometer powerful for portable in situ applications. In the encoding part of the computational spectrometer, filters with highly non-correlated properties are requisite for compressed sensing, which ...
Haojie Liao, Lin Yang, Yuanhao Zheng, Yansong Wang   +3 more
doaj   +1 more source

Correlated optical convolutional neural network with “quantum speedup”

Light: Science & Applications
Compared with electrical neural networks, optical neural networks (ONNs) have the potentials to break the limit of the bandwidth and reduce the consumption of energy, and therefore draw much attention in recent years.
Yifan Sun, Qian Li, Ling-Jun Kong, Xiangdong Zhang   +3 more
doaj   +1 more source

Generative Adversarial Optical Networks Using Diffractive Layers for Digit and Action Generation

Photonics
Within the traditional electronic neural network framework, Generative Adversarial Networks (GANs) have achieved extensive applications across multiple domains, including image synthesis, style transfer and data augmentation.
Pei Hu, Tengyu Cui, Yuanyuan Zhang, Shuai Feng   +3 more
doaj   +1 more source

Refractive index tomography with a physics-based optical neural network. [PDF]

Biomed Opt Express, 2023
Yang D, Zhang S, Zheng C, Zhou G, Hu Y, Hao Q.   +5 more
europepmc   +1 more source

Ultra-compact multi-task processor based on in-memory optical computing

Light: Science & Applications
To enhance the computational density and energy efficiency of on-chip neuromorphic hardware, this study introduces a novel network architecture for multi-task processing with in-memory optical computing. On-chip optical neural networks are celebrated for
Wencan Liu, Yuyao Huang, Run Sun, Tingzhao Fu, Sigang Yang, Hongwei Chen   +5 more
doaj   +1 more source

Wing Load and Angle of Attack Identification by Integrating Optical Fiber Sensing and Neural Network Approach in Wind Tunnel Test

Applied Sciences, 2019
The load and angle of attack (AoA) for wing structures are critical parameters to be monitored for efficient operation of an aircraft. This study presents wing load and AoA identification techniques by integrating an optical fiber sensing technique and a
Daichi Wada, Masato Tamayama
doaj   +1 more source

Human emotion recognition with a microcomb-enabled integrated optical neural network. [PDF]

Nanophotonics, 2023
Cheng J, Xie Y, Liu Y, Song J, Liu X, He Z, Zhang W, Han X, Zhou H, Zhou K, Zhou H, Dong J, Zhang X.   +12 more
europepmc   +1 more source