Adaptive Demodulator Using Machine Learning for Orbital Angular Momentum Shift Keying
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- Type
- article
- Published
- 2017-09-01
- Cited by
- 79
- References
- 20
- OpenAlex
- https://openalex.org/W2735927552
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:28229323
Keywords
Demodulation, Computer science, Artificial intelligence, Adaptive optics, Convolutional neural network
References
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- Pattern Recognition and Machine Learning
- Sidelobe-modulated optical vortices for free-space communication.
- Terabit free-space data transmission employing orbital angular momentum multiplexing
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- Learning Hierarchical Features for Scene Labeling
- Massive individual orbital angular momentum channels for multiplexing enabled by Dammann gratings
- Distributed hierarchical processing in the primate cerebral cortex.
- Influence of atmospheric turbulence on the propagation of quantum states of light carrying orbital angular momentum.
- ImageNet classification with deep convolutional neural networks
- Aberration corrections for free-space optical communications in atmosphere turbulence using orbital angular momentum states.
- Deep Neural Networks for Acoustic Modeling in Speech Recognition
- Nonlinear decision boundary created by a machine learning-based classifier to mitigate nonlinear phase noise
- Combatting nonlinear phase noise in coherent optical systems with an optimized decision processor based on machine learning
- Nonlinearity Mitigation Using a Machine Learning Detector Based on k -Nearest Neighbors
- Top Downloads in IEEE Xplore [Reader's Choice]
- System impairment compensation in coherent optical communications by using a bio-inspired detector based on artificial neural network and genetic algorithm
- Sequence to Sequence Learning with Neural Networks
- Deep Learning
- Buffalo Medical and Surgical Journal: Book Reviews
Cited by
- Communicating Using Spatial Mode Multiplexing: Potentials, Challenges, and Perspectives
- Direct detection receiver for vortex beam.
- Analysis of an adaptive orbital angular momentum shift keying decoder based on machine learning under oceanic turbulence channels
- Turbo-coded 16-ary OAM shift keying FSO communication system combining the CNN-based adaptive demodulator.
- Coherently demodulated orbital angular momentum shift keying system using a CNN-based image identifier as demodulator
- Mode detection of misaligned orbital angular momentum beams based on convolutional neural network.
- Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
- Orbital angular momentum detection based on diffractive deep neural network
- Efficient Recognition of the Propagated Orbital Angular Momentum Modes in Turbulences With the Convolutional Neural Network
- Deep learning based atmospheric turbulence compensation for orbital angular momentum beam distortion and communication.
- Deep learning based adaptive sequential data augmentation technique for the optical network traffic synthesis.
- Experimental study of machine-learning-based orbital angular momentum shift keying decoders in optical underwater channels
- Dealing With Alarms in Optical Networks Using an Intelligent System
- Comprehensive study of orbital angular momentum shift keying systems with a CNN-based image identifier
- Detecting Orbital Angular Momentum Modes of Vortex Beams Using Feed-Forward Neural Network
- Deep Learning for channel estimation in FSO communication system
- OAM mode recognition based on joint scheme of combining the Gerchberg–Saxton (GS) algorithm and convolutional neural network (CNN)
- Adaptive Demodulation Technique for Efficiently Detecting Orbital Angular Momentum (OAM) Modes Based on the Improved Convolutional Neural Network
- Identification of hybrid orbital angular momentum modes with deep feedforward neural network
- Atmospheric turbulence compensation with sensorless AO in OAM-FSO combining the deep learning-based demodulator
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