Results 11 to 20 of about 1,530,208 (226)
Deep learning for minimum mean-square error approaches to speech enhancement
Speech Communication, 2019 Recently, the focus of speech enhancement research has shifted from minimum mean-square error (MMSE) approaches, like the MMSE short-time spectral amplitude (MMSE-STSA) estimator, to state-of-the-art masking- and mapping-based deep learning approaches ...
Aaron Nicolson, K. Paliwal
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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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Modeling of Activated Sludge Process Using Multi-Layer Perceptron Neural Networks [PDF]
Nature Environment and Pollution Technology, 2023 Mathematical Modeling of the activated sludge process (ASP) enhances the understanding of the process and improves the quality of the effluent released.
Saurabh Sahadev , G. Madhu and M. Roy Thomas
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Recursive Polynomial Minimum Mean-Square Error Estimation with Applications to Orbit Determination
Journal of Guidance Control and Dynamics, 2020 This paper presents a systematic generalization of the linear update structure associated with the extended Kalman filter for high-order polynomial estimation of nonlinear dynamical systems.
Simone Servadio, R. Zanetti
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Minimum Mean Squared Error interference alignment [PDF]
2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, 2009 To achieve the full multiplexing gain of MIMO interference networks at high SNRs, the interference from different transmitters must be aligned in lower-dimensional subspaces at the receivers. Recently a distributed “max-SINR” algorithm for precoder optimization has been proposed that achieves interference alignment for sufficiently high SNRs.
David A. Schmidt +4 more
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Performance analysis of V-BLAST signal detection algorithm in MIMO system
上海师范大学学报. 自然科学版, 2021 In this paper, the commonly used minimum mean square error algorithm, zero-forcing detection algorithm, nonlinear detection algorithm and orthogonal triangular decomposition detection algorithm in the vertical layered space-time detection algorithm were ...
ZHANG Ming +3 more
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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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New Journal of Physics, 2023 Quantum state tomography (QST) is essential for characterizing unknown quantum states. Several methods of estimating quantum states already exist and can be classified mainly into three broad classes.
Subhadeep Mondal, Amit Kumar Dutta
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Minimum mean square error estimation [PDF]
Applications of Mathematics, 1979 In many cases we can consider the regression parameters as realizations of a random variable. In these situations the minimum mean square error estimator seems to be useful and important. The explicit form of this estimator is given in the case that both the covariance matrices of the random parameters and those of the error vector are singular.
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Entropy, 2022 Multiple-input Multiple-Output (MIMO) systems require orthogonal frequency division multiplexing to operate efficiently in multipath communication (OFDM).
Dhanasekaran S +5 more
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