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Single image noise level estimation by artificial noise
Signal Processing, 2023Fang Li 0004 +3 more
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Reducing noise in photoamplifier circuits with low noise artificial resistors
Journal of Applied Physics, 1982A standard passive dissipative resistor in a photodiode circuit is replaced by a low-noise active artificial resistor. A room-temperature artificial resistor acts on a signal current from the photodiode in the same manner as the resistor, but the self-generated noise of the artificial resistor is that of a resistor at cryogenic temperatures. Because of
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Artificial noise-aided secure beamforming for multigroup multicast
2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2018We investigate the physical layer security for multiple-input single-output (MISO) multigroup multicast system in the presence of multiple eavesdroppers (Eves). To elaborate, we aim to tackle the secrecy rate maximization (SRM) problem of the multicast system by proposing an algorithm for secure beam-forming.
Wanjik Kim +3 more
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Secrecy signal and artificial noise designs in cellular network
2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP), 2015In this paper, we propose a new method of secrecy signal and artificial noise (AN) transmission for a MISO wiretap channel in wireless cellular networks. We first design the secrecy signal beamformer such that its power leakage to the unintended directions is minimized, then we concentrate the AN on the directions with higher risk of information ...
Huiming Wang 0001, Feng Liu
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Preventing Eavesdropper by Artificial Noise in MIMO-OFDM Systems
Wireless Personal Communications, 2018The PHY security has been the focus of the researchers since the day it was proposed. The researchers have mentioned many kinds of methods to prevent the eavesdropper from overhearing the confidential signal in different types of networks and environments. However, none of them have proposed a method which can be used in MIMO-OFDM.
Tao Jing +3 more
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Regularization and Feedforward artificial neural network training with noise
Proceedings of the International Joint Conference on Neural Networks, 2003., 2004Regularization is a method used for controlling the complexity of models. Explicit regularization uses a modifier term, incorporating a-priori knowledge about the function to be approximated by Feedforward Artificial Networks, that is added to the risk functional and implicit regularization where noise is added to the system variables during training ...
Pravin Chandra, Yogesh Singh
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Fingerprint Embedding Authentication with Artificial Noise: MISO Regime
2019 IEEE Conference on Communications and Network Security (CNS), 2019We apply artificial noise to the fingerprint embedding authentication framework to improve information-theoretic authentication for the MISO channel. Instead of optimizing for secrecy capacity, we examine the trade-off between message rate, authentication, and key security.
Jake Bailey Perazzone +3 more
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PIV Measurements of Buffet with Artificial Noise
2017The transonic buffet flow field around supercritical airfoils is dominated by self-sustained shock wave oscillations on the suction side of the wing. Current theories assume that this unsteadiness is driven by a feedback loop of disturbances in the flow field downstream of the shock wave of which the upstream propagating part is formed by acoustic ...
Antje Feldhusen-Hoffmann +2 more
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Modeling Environmental Noise Using Artificial Neural Networks
2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009Since 1972, when the World Health Organization (WHO) classified noise as a pollutant, most industrialized countries have enacted laws or local regulations that regulate noise levels. Many scientists have tried to model urban noise, but the results have not been as good as expected because of the reduced number of variables.
N. Genaro +5 more
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Noise Optimization in Artificial Neural Networks
2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), 2022Li Xiao 0005 +3 more
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