Performance and Analysis of Recursive Constrained Least Lncosh Algorithm Under Impulsive Noises

Liang, Tao; Li, Yingsong; Xue, Wei; Jiang, Tao

doi:10.1109/tcsii.2020.3037877

Cited by 55 publications

(11 citation statements)

References 26 publications

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“…The parameter µ is listed in the Figs. 4. We can conclude that when λ is too small or too large, LNAF's performance becomes worse for WGN and AR input signals, and the LNAF algorithm achieves the best performance for λ = 0.7 and p = 0.…”

Section: A Echo Channel Estimationmentioning

confidence: 77%

“…T HE echo is experienced in numerous transmission systems such as vehicle information and video teleconferencing strategies [1]- [3], which will decline the quality of voice transmissions. Adaptive filtering (AF), which is commonly employed for noise reductions in varied situations and has been paid more concerns in recent decades, is an effective method to exclude ambient noises [4]- [9]. The weight updating equations are important for AF algorithms, which are obtained from the derivation of various cost functions constructed using different error criterions.…”

Section: Introductionmentioning

confidence: 99%

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Lawson-Norm Based Adaptive Filter for Channel Estimation and in-Car Echo Cancellation

Li¹

2022

Preprint

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<div>We proposed a Lawson-norm-based adaptive estimation algorithm within the affine-project theory framework and give a name of Lawson-norm adaptive filter (LNAF) algorithm. The LNAF algorithm is derived, analyzed, and simulated for echo cancellation when background noise is impulsive, which is realized and implemented via using Lawson norm of past errors to take a sliding window on cost function to speed up convergence and achieve robustness for impulsive noises for colored signal. Simulations based on measured data are used for in-car echo cancellation and channel estimation to verify the LNAF algorithm's performance with different inputs, which prove that the LNAF algorithm is superior to the popular AP algorithms under differnt impulsive interferences.</div><div><br></div>

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Section: A Echo Channel Estimationmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Lawson-Norm Based Adaptive Filter for Channel Estimation and in-Car Echo Cancellation

Li¹

2022

Preprint

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“…In addition, the adaptive interference suppression for PD radar can be considered using adaptive filtering [19][20][21][22][23][24][25][26][27][28] and sparse arrays [29][30][31].…”

Section: Simulation and Measurement Resultsmentioning

confidence: 99%

Speed Interference Suppression for PD Radar Based on Adaptive Dictionary

Zhang

et al. 2022

ACES Journal

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Random pulse initial phase (RPIP) signal is a kind of agility waveform which is commonly used in pulse Doppler (PD) radar. Although RPIP has the merit of restraining velocity deception jamming effectively, its efficiency is restricted under the condition of strong interference. To make the RPIP signal fully play the anti-jamming performance, this paper proposed a speed interference suppression method based on adaptive dictionar that separates the target echo from the strong jamming signal with good sparsity. First, the prior knowledge of strong interference signal is obtained by the technique of peak detection which is combined with the dual channel processing. Second, the quasi-Karhunen-Loeve transform (Q-KLT) basis of interference signal is constructed based on the prior knowledge, and the approximate Q-KLT basis of target signal is constructed by the way of dictionary learning, and those signals can be obtained from the adaptive dictionary by the algorithm of base tracking (BP). Finally, the effectiveness of the proposed method is verified by numerical simulation, which proves that the method can ensure a lower Doppler sidelobe in the strong interference scene, which confirmed that it has a good anti-velocity deception performance.

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“…Furthermore, the non-Gaussian distributed signals are frequently encountered in many practical applications [8,11,12,16,17,18], and the performance of the MSE-based algorithms might degrade in the non-Gaussian noise environments, especially in the heavy-tailed noises [16,17,18,19,20]. To improve the convergence performance in the presence of non-Gaussian noises, various alternative error criterions and cost functions are proposed and discussed, such as mean absolute error (MAE) [16], maximum correntropy criterion (MCC) [17,18] and Lncosh function [11,21,22,23,24].…”

Section: Introductionmentioning

confidence: 99%

Transient Convergence Analysis of Least Lncosh Algorithm

Sun¹,

Li²

2022

Preprint

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<p>Lncosh function has been used for constructing a cost function for devising an adaptive filter algorithm to provide a desired performance under non-Gaussian noise, naming as least Lncosh algorithm (LLA). However, its transient behavior analysis has not been analyzed and investigated. As an important characteristic for the LLA, the transient behavior affects its performance in real-world applications. Herein, we present the theoretical model for evaluating the mean weight behavior and the transient excess mean square error (EMSE) behavior of the LLA. In addition, the proposed models can also be used to predict the transient behavior of the adaptive filtering algorithms with error nonlinearities {under non-Gaussian noises}. The experiment results have verified the validity of the presented models.</p> <p><br></p>

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Performance and Analysis of Recursive Constrained Least Lncosh Algorithm Under Impulsive Noises

Cited by 55 publications

References 26 publications

Lawson-Norm Based Adaptive Filter for Channel Estimation and in-Car Echo Cancellation

Lawson-Norm Based Adaptive Filter for Channel Estimation and in-Car Echo Cancellation

Speed Interference Suppression for PD Radar Based on Adaptive Dictionary

Transient Convergence Analysis of Least Lncosh Algorithm

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