Improved proportionate-type sparse adaptive filtering under maximum correntropy criterion in impulsive noise environments

Gogineni, Vinay Chakravarthi; Mula, Subrahmanyam

doi:10.1016/j.dsp.2018.04.011

Cited by 28 publications

(6 citation statements)

References 28 publications

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“…Proof: Substituing ε = 0 into (17) and using (10)−(12) along with some tedious derivations, we can obtain the expression (22). Similarly, the results (23), (24) and (25) follow readily by replacing the parameters in (22) with the corresponding counterparts.…”

Section: Theorem 1: Letmentioning

confidence: 94%

Statistical Properties of Average Kendall’s Tau Under Multivariate Contaminated Gaussian Model

Lai

2019

IEEE Access

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In this paper, we derived the analytical forms of the expectation and variance of average Kendall's tau (AKT) under a specific multivariate contaminated Gaussian model (MCGM), which can simulate a scenario where the multi-channel noise exhibits an impulsive manner. For a better understanding of AKT, we compared AKT to other two classical concordance correlation coefficients, i.e., Kendall's concordance coefficient (KCC), and the average Pearson's product moment correlation coefficient (APPMCC) with respect to the root mean squared error (RMSE). We also applied AKT, KCC and APPMCC to the problem of multi-channel random signal detection. Monte Carlo simulations not only validated our theoretical findings, but also revealed the advantage of AKT over KCC and APPMCC in terms of the receiver operating characteristic (ROC) curves. INDEX TERMS Average Kendall's tau (AKT), multivariate contaminated Gaussian model (MCGM), root mean squared error (RMSE), multi-channel signal detection, receiver operating characteristic (ROC) curve.

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Section: Theorem 1: Letmentioning

confidence: 94%

Statistical Properties of Average Kendall’s Tau Under Multivariate Contaminated Gaussian Model

Lai

2019

IEEE Access

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“…delayed MPLMS (DMPLMS) and delayed WMPNLMS (DWMPLMS) as shown in [25]. It is to be mentioned that an approach was proposed for building the algorithm in maximum correntropy criterion (MCC) in [26] which was a good choice under impulsive environments in terms of cost but it was outperformed by its successor improved MCC (IP-MCC) in [27].…”

Section: Introductionmentioning

confidence: 99%

“…The next approach to algorithms is derived purely from the above-mentioned algorithms namely LLAD [6], QK-LMS [8], IP-MCC [27] and SLMS [7], in which the delayed concept [9] with its constraints [10] and the retiming approach [15] with the MPNLMS [22] algorithm are very well combined to derive delayed μ-law Proportionate LLAD (DMPLLAD), delayed μ-law proportionate QK-LMS (DMPQK-LMS), delayed μ-law proportionate MCC (DMPMCC) and delayed μ-law proportionate sign-LMS (DMPSLMS) [28] provide a good convergence rate and also exhibit robustness against impulsive responses. Our contributions in the paper includes, Obtaining good performance and convergence rate by proposing an efficient algorithm by combining the delayed μ-law proportionate (DMP) and least mean logarithmic square (LMLS) algorithms i.e.…”

Section: Introductionmentioning

confidence: 99%

Delay-power efficient VLSI architecture design for robust proportionate adaptive filter

Lakshmaiah

Narayanappa

Narasimhaiah³

et al. 2022

IJEECS

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This paper proposes <span lang="EN-US">the robust proportionate adaptive filtering algorithms and their respective efficient very large-scale integration (VLSI) architectures for sparse system identification under impulsive noise, several types of algorithms are combined to obtain optimum results. Here, we rendered a relative analysis on these algorithms and the algorithms are mapped on to the hardware to show that the improvement is obtained with respect to convergence rate and hardware complexity of VLSI architectures and has negligible hardware overhead with improved robustness. Good performance and convergence rate is obtained by combining the delayed μ-law proportionate (DMP) and least mean logarithmic square (LMLS) algorithms i.e. delayed µ-law proportionate least mean logarithmic square (DMP LMLS). Robust proportionate adaptive filter is coded in system verilog and synthesized using cadence genus compiler with 90 nm technology library.</span>

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“…For example, the channels of UAC have sparse characteristics [22]. Some relevant adaptive filtering algorithms are studied for this problem, and the work in [23] incorporated MCC into the proportionate-type adaptive filtering to develop a proportionate MCC (PMCC) algorithm for sparse system identification, while the work in [24] improved the convergence speed with the underlying system sparsity.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Filtering Algorithm for Self-Interference Cancellation with Impulsive Noise

Zhang

Shi

et al. 2021

Electronics

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Self-interference (SI) is usually generated by the simultaneous transmission and reception in the same system, and the variable SI channel and impulsive noise make it difficult to eliminate. Therefore, this paper proposes an adaptive digital SI cancellation algorithm, which is an improved normalized sub-band adaptive filtering (NSAF) algorithm based on the sparsity of the SI channel and the arctangent cost function. The weight vector is hardly updated when the impulsive noise occurs, and the iteration error resulting from impulsive noise is significantly reduced. Another major factor affecting the performance of SI cancellation is the variable SI channel. To solve this problem, the sparsity of the SI channel is estimated with the estimation of the weight vector at each iteration, and it is used to adjust the weight vector. Then, the convergence performance and calculation complexity are analyzed theoretically. Simulation results indicate that the proposed algorithm has better performance than the referenced algorithms.

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Improved proportionate-type sparse adaptive filtering under maximum correntropy criterion in impulsive noise environments

Cited by 28 publications

References 28 publications

Statistical Properties of Average Kendall’s Tau Under Multivariate Contaminated Gaussian Model

Statistical Properties of Average Kendall’s Tau Under Multivariate Contaminated Gaussian Model

Delay-power efficient VLSI architecture design for robust proportionate adaptive filter

Robust Adaptive Filtering Algorithm for Self-Interference Cancellation with Impulsive Noise

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