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Augmented GNSS Differential Corrections Minimum Mean Square Error Estimation Sensitivity to Spatial Correlation Modeling Errors [PDF]
Sensors, 2014 Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS)
Nazelie Kassabian +2 more
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Reducing normalized mean square error during channel estimation using minimum pilot symbols in massive MIMO network [PDF]
Scientific ReportsDeep Learning technology has emerged as an exciting innovation in the field of applications in wireless communications systems. In this proposed work, fully connected neural network based on deep learning (DL-FCNN) as well as convolutional neural network
Swapna Tangelapalli +5 more
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Bayesian minimum mean square error for transmissivity sensing
Physical Review Research, 2023 We address the problem of estimating the transmissivity of the pure-loss single-mode bosonic channel from the Bayesian point of view, i.e., when a prior probability distribution function (PDF) on the transmissivity is available.
Boyu Zhou +3 more
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Sensors, 2023 This paper discusses the results of simulations relating to the performances of turbo codes, low density parity check (LDPC) codes, and polar codes over an additive white Gaussian noise (AWGN) channel in the presence of inter symbol interference ...
Adriana-Maria Cuc +2 more
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IET Communications, 2021 This paper addresses the problem of minimum mean square error channel estimator for time division duplex massive multi‐user multi‐input multi‐output systems. It is noteworthy that, the minimum mean square error has been previously proposed for multi‐cell
Muamer Hawej, Yousef R. Shayan
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Approximate Formulas for the Gamma Function with Positive Argument [PDF]
The Egyptian Statistical Journal, 1991 This paper introduces four approximate formulas for calculating r (x), x ε R+. They produce approximate values which are "very close " to the tabulated ones. One of the formulas gives correct results up to at least five decimal places.
Abdul-Mordy Azzam, Yehia Abbas
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International Journal of Distributed Sensor Networks, 2022 One of the fundamental problems in sensor networks is to estimate and track the target states of interest that evolve in the sensing field. Distributed filtering is an effective tool to deal with state estimation in which each sensor only communicates ...
Teng Shao
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Where Does Minimum Error Entropy Outperform Minimum Mean Square Error? A New and Closer Look
IEEE Access, 2018 The past decade has seen a rapid application of information theoretic learning (ITL) criteria in robust signal processing and machine learning problems. Generally, in ITL's literature, it is seen that, under non-Gaussian assumptions, especially when the ...
Ahmad Reza Heravi, Ghosheh Abed Hodtani
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Scalable kernel-based minimum mean square error estimate for light-field image compression
EURASIP Journal on Image and Video Processing, 2018 Light-field imaging can capture both spatial and angular information of a 3D scene and is considered as a prospective acquisition and display solution to supply a more natural and fatigue-free 3D visualization.
Zhixiang You, Ping An, Deyang Liu
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IEEE Access, 2020 For linear dynamic systems with Gaussian noise, the Kalman filter provides the Minimum Mean-Square Error (MMSE) state estimation by tracking the posterior. Similarly, for systems with Gaussian Mixture (GM) noise distributions, a bank of Kalman filters or
Leila Pishdad, Fabrice Labeau
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