VFF ‐norm penalised WL‐RLS algorithm using DCD iterations for underwater acoustic communication

Lu, Lipeng; Zhang, Youwen; Sun, Dong

doi:10.1049/iet-com.2016.1012

Cited by 11 publications

(8 citation statements)

References 27 publications

(42 reference statements)

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“…As to the use of the 1 -norm, the proposed approach is different from sparse systems estimation methods, where the penalty is directly imposed on the filter coefficients vector, as in the LASSO algorithm, with application to compressive sensing [15], network identification [16] [17], sparse channel estimation [18] [19], and beamforming design [20].…”

Section: Accepted Manuscriptmentioning

confidence: 99%

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Mixed ℓ 2 and ℓ 1 -norm regularization for adaptive detrending with ARMA modeling

Giarré

Argenti

2018

Journal of the Franklin Institute

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Section: Accepted Manuscriptmentioning

confidence: 99%

“…From the observation of ( 19), we can see that, unlike [22], the 1 -norm is not applied to the parameter vector, but rather the cost function depends on the absolute value of a linear combination of the parameters to be optimized. The rule that minimizes (19) at each step coincides with the following parameter vector updating:…”

Section: Lms Solutionmentioning

confidence: 99%

Mixed ℓ 2 and ℓ 1 -norm regularization for adaptive detrending with ARMA modeling

Giarré

Argenti

2018

Journal of the Franklin Institute

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“…In many signal processing applications [1][2][3][4], we find various sparse channels in which most of the impulse responses are close to zero and only some of them are large. In recent years, many kinds of sparse adaptive filtering algorithms have been proposed for sparse system estimation, including recursive least squares (RLS)-based [5][6][7][8][9] and least mean square (LMS)-based algorithms [10][11][12][13][14]. It is generally known that RLS-based algorithms have faster convergence and less error after convergence than LMS-based algorithms [15].…”

Section: Introductionmentioning

confidence: 99%

Maximum Correntropy Criterion Based l1-Iterative Wiener Filter for Sparse Channel Estimation Robust to Impulsive Noise

Lim

2020

Applied Sciences

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In this paper, we propose a new sparse channel estimator robust to impulsive noise environments. For this kind of estimator, the convex regularized recursive maximum correntropy (CR-RMC) algorithm has been proposed. However, this method requires information about the true sparse channel to find the regularization coefficient for the convex regularization penalty term. In addition, the CR-RMC has a numerical instability in the finite-precision cases that is linked to the inversion of the auto-covariance matrix. We propose a new method for sparse channel estimation robust to impulsive noise environments using an iterative Wiener filter. The proposed algorithm does not need information about the true sparse channel to obtain the regularization coefficient for the convex regularization penalty term. It is also numerically more robust, because it does not require the inverse of the auto-covariance matrix.

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“…synthesized In 2 (O,S) 3 oxysulfide for the Cr (VI) detoxification and hydrogen evolution reaction (HER). Liu prepared nickel cobalt oxysulfide (CoNi)O x S y for a high‐performance electrode material of super‐capacitors. Park et al .…”

Section: Introductionmentioning

confidence: 99%

Tubular bimetal oxysulfide CuMgOS catalyst for rapid reduction of heavy metals and organic dyes

Chen

Kuo

Zhang

et al. 2019

Applied Organom Chemis

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Tubular bimetal oxysulfide CuMgOS catalyst was prepared using a feasible method at a low process temperature of 95°C. X‐ray diffractometry, X‐ray photoelectron spectrometry, field emission‐scanning electron microscopy, transmission electron microscopy, UV–Vis diffuse reflectance spectroscopy, photoluminescence emission spectrum, and nitrogen adsorption–desorption isotherms were used for CuMgOS characterizations. The CuMgOS reduction activities were investigated through the reduction of heavy metals of Cr (VI), Pb (II) and Hg (II) solutions, and the organic dyes of rhodamine‐B (RhB), methyl orange (MO) and methylene blue (MB) solutions under dark. The results showed that the CuMgOS prepared with an appropriate N2H4 amount for a suitable Cu (I)/Cu (II) ratio exhibited fast reduction activity without adding any reagents, with which the 100 mL Cr (VI), Pb (II) and Hg (II) solutions of 50 ppm were 100% reduced by 20 mg CuMgOS within 4 min, 6 min and 4 min, respectively. The 100 mL RhB, MO and MB solutions of 50 ppm were 100% reduced by 10 mg CuMgOS within 4 min, 5 min and 1 min, respectively, under the existence of NaBH4. CuMgOS displayed excellent chemical stability for the re‐use tests on heavy metal ions and organic dyes. The excellent performance is attributed to CuMgOS bimetal oxysulfide catalyst with active surface reaction centers to interact with reactants, and the carrier hopping between Cu (I) and Cu (II).

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VFF ‐norm penalised WL‐RLS algorithm using DCD iterations for underwater acoustic communication

Cited by 11 publications

References 27 publications

Mixed ℓ 2 and ℓ 1 -norm regularization for adaptive detrending with ARMA modeling

Mixed ℓ 2 and ℓ 1 -norm regularization for adaptive detrending with ARMA modeling

Maximum Correntropy Criterion Based l1-Iterative Wiener Filter for Sparse Channel Estimation Robust to Impulsive Noise

Tubular bimetal oxysulfide CuMgOS catalyst for rapid reduction of heavy metals and organic dyes

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