Results 11 to 20 of about 7,242,720 (244)
Neural Network Calculations at the Speed of Light Using Optical Vector-Matrix Multiplication and Optoelectronic Activation [PDF]
, 2021 With the rapid progress of the integrated nanophotonics technology, the optical neural network architecture has been widely investigated. Since the optical neural network can complete the inference processing just by propagating the optical signal in the
NOTOMI, Masaya +5 more
core +1 more source
Optical neural networks: The 3D connection [PDF]
Photoniques, 2020 We motivate a canonical strategy for integrating photonic neural networks (NN) by leveraging 3D printing. Our belief is that a NN’s parallel and dense connectivity is not scalable without 3D integration. 3D additive fabrication complemented with photonic signal transduction can dramatically augment the current capabilities of 2D CMOS and integrated ...
Dinc, Niyazi Ulas +2 more
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Single-shot optical neural network
Science Advances, 2023 Analog optical and electronic hardware has emerged as a promising alternative to digital electronics to improve the efficiency of deep neural networks (DNNs). However, previous work has been limited in scalability (input vector lengthK≈ 100 elements) or has required nonstandard DNN models and retraining, hindering widespread adoption.
Liane Bernstein +5 more
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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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Low-depth optical neural networks
Chip, 2022 Optical neural network (ONN) is emerging as an attractive proposal for machine-learning applications, enabling high-speed computation with low-energy consumption. However, there are several challenges in applying ONN for industrial applications, including the realization of activation functions and maintaining stability. In particular, the stability of
Xiao-Ming Zhang, Man-Hong Yung
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Neural-network-based MDG and Optical SNR Estimation in SDM Transmission
, 2021 We propose a neural network model for MDG and optical SNR estimation in SDM transmission. We show that the proposed neural-network-based solution estimates MDG and SNR with high accuracy and low complexity from features extracted after ...
Chigo Okonkwo (7195016) +4 more
core +2 more sources
Implementation of Pruned Backpropagation Neural Network Based on Photonic Integrated Circuits
Photonics, 2021 We demonstrate a pruned high-speed and energy-efficient optical backpropagation (BP) neural network. The micro-ring resonator (MRR) banks, as the core of the weight matrix operation, are used for large-scale weighted summation.
Qi Zhang, Zhuangzhuang Xing, Duan Huang
doaj +1 more source
Adversarial Attacks on an Optical Neural Network
IEEE Journal of Selected Topics in Quantum Electronics, 2023 Adversarial attacks have been extensively investigated for machine learning systems including deep learning in the digital domain. However, the adversarial attacks on optical neural networks (ONN) have been seldom considered previously. In this work, we first construct an accurate image classifier with an ONN using a mesh of interconnected Mach-Zehnder
Shuming Jiao, Ziwei Song, Shuiying Xiang
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Optical Soliton Neural Networks
, 2023 The chapter describes the realization of photonic integrated circuits based on photorefractive solitonic waveguides. In particular, it has been shown that X-junctions formed by soliton waveguides can learn information by switching their state. X junctions can perform both supervised and unsupervised learning.
Eugenio Fazio +2 more
openaire +2 more sources
Scientific Reports, 2023 Microstructures with engineered properties are critical to thermal management in aerospace and space applications. Due to the overwhelming number of microstructure design variables, traditional approaches to material optimization can have time-consuming ...
Jonathan Sullivan +2 more
doaj +1 more source