Results 11 to 20 of about 146,825 (261)
Heritage and Sustainable Development, 2023 The highest rate at which information may be reliably sent via a communication link is known as its capacity. In the case of non-Gaussian noise, the capacity of the channel depends on the specific characteristics of the noise, which can cause severe ...
Ghanim A. Al-Rubaye +2 more
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Beyond Gaussian Noise: A Generalized Approach to Likelihood Analysis with Non-Gaussian Noise
The Astrophysical Journal Letters, 2023 Likelihood analysis is typically limited to normally distributed noise due to the difficulty of determining the probability density function of complex, high-dimensional, non-Gaussian, and anisotropic noise.
Ronan Legin +3 more
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环境与职业医学, 2022 BackgroundOccupational noise-induced hearing loss (NIHL) is one of the most prevalent occupational diseases in the world. With the development of industry, noise sources in the workplace have become increasingly complex.ObjectiveTo apply kurtosis ...
Jiarui XIN +7 more
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Remote Sensing, 2023 Non-Gaussian impulsive noise in marine environments strongly influences the detection of weak spectral lines. However, existing detection algorithms based on the Gaussian noise model are futile under non-Gaussian impulsive noise.
Zhen Li, Junyuan Guo, Xiaohan Wang
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IEEE Access, 2020 Mechanical signals are not only disturbed by Gaussian noise, but also by non-Gaussian noise. These Gaussian noise and non-Gaussian noise have gravely impeded detecting of rolling bearing defects using traditional methods.
Yonghua Jiang +5 more
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Channel-noise tracking for sub-shot-noise-limited receivers with neural networks
Physical Review Research, 2021 Non-Gaussian receivers for optical communication with coherent states can achieve measurement sensitivities beyond the limits of conventional detection, given by the quantum-noise limit (QNL).
M. T. DiMario, F. E. Becerra
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Non-Gaussianity of Stochastic Gradient Noise
CoRR, 2019 What enables Stochastic Gradient Descent (SGD) to achieve better generalization than Gradient Descent (GD) in Neural Network training? This question has attracted much attention. In this paper, we study the distribution of the Stochastic Gradient Noise (SGN) vectors during the training. We observe that for batch sizes 256 and above, the distribution is
Abhishek Panigrahi +3 more
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Compressed matched filter for non-Gaussian noise [PDF]
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014 We consider estimation of a deterministic unknown parameter vector in a linear model with non-Gaussian noise. In the Gaussian case, dimensionality reduction via a linear matched filter provides a simple low dimensional sufficient statistic which can be easily communicated and/or stored for future inference.
Jakob Vovnoboy, Ami Wiesel
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Impact of the non-Gaussian measurement noise on the performance of state-of-the-art state estimators for distribution systems [PDF]
Serbian Journal of Electrical EngineeringThis paper aims to investigate the impact of non-Gaussian measurement noise on state estimation (SE) results in distribution systems. To this end, the measurement noise is assumed to be distributed according to Gaussian or one of the following ...
Čubonović Stefan +2 more
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Generalized Maximum Correntropy Kalman Filter for Target Tracking in TianGong-2 Space Laboratory
Space: Science & Technology, 2022 Target tracking plays an important role in the construction, operation, and maintenance of the space station by the robot, which puts forward high requirements on the accuracy of target tracking.
Yang Mo +5 more
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