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We consider the problem of estimating a signal subspace in the presence of interference that contaminates some proportion of the received observations. Our emphasis is on detecting the contaminated observations so that the signal subspace can be ...

This article presents a way to improve the Diffusion LMS algorithm in practical scenarios while maintaining data privacy. It focuses on reducing external errors and ensuring accurate estimation of the parameter vector through distributed and ...

The widely linear complex-valued least mean square (WL-CNLMS) algorithm is extensively used for processing complex-valued signals, but it exists performance compromise between convergence rate and steady-state misadjustment. In response to this ...

As an adaptive finite impulse response filtering algorithm, the maximum total correntropy (MTC) algorithm plays an important role in parameter estimation of the errors-in-variables model where both input and output signals are contaminated with ...$$

The performance of conventional active noise control (ANC) systems degrades under non-Gaussian conditions. In the recent past, generalized filtered-x maximum correntropy criterion (FxGMCC) algorithm has been widely used to tackle such non-...

• A robust FxEHCAF algorithm based ANC technique is proposed.
• Affine-FxEHCAF algorithm for enhanced noise control is also proposed.
• The theoretical analysis of FxEHCAF and Affine-FxEHCAF are carried out.
• Proposed algorithms ...

This study introduces a variable diagonal-matrix-step-size affine projection algorithm (APA), which shows robustness against to impulsive noises. Unlike the normal scalar step-size method, the independent step size for each input vector is used ...

• Novel robust affine projection algorithm for recursive estimation.
• Efficient system identification algorithm in an impulsive noise environment.
• Calculation of optimal step size that improves convergence performance.
• Adaptive ...

Digital communication systems usually suffer from two factors: inter-symbol interference and impulsive noise. To improve the performance of communication receivers, this paper proposes a good solution to a linear blind equalizer. Firstly, a new ...

While the practical application of adaptive filters has indeed garnered substantial attention, two pressing issues persist that have a profound impact on their performance—system sparsity and the presence of contaminated Gaussian impulsive noise. ...

The filtered-x least mean square (F-xLMS) technique dependent distributed active noise control (DANC) system is less effective against outliers and disturbances that represent impulses. In such an environment, DANC algorithms based on Swish ...

As a blind equalization algorithm, the fractional lower-order statistics based multimodulus algorithm (FLOS-MMA) is suitable for equalizing multilevel quadrature amplitude modulation (QAM) signals in impulsive noise. However, the equalization ...

Distributed inference tasks could be performed by adaptive filtering techniques. Several enhancement strategies for such techniques were proposed, such as sparsity-aware algorithms, coefficients reuse and correntropy-based cost functions in the ...

In the past decade, the augmented complex-valued least mean square adaptive filtering algorithm based on the minimum mean square error criterion and widely-linear model has attracted much attentions due to its simplicity and applicability to non-...

In the scerinao of impulsive noise, this paper proposes a multi-Bernoulli enhanced auxiliary particle filtering (MB-EAPF) algorithm for multi-source direction of arrival tracking by utilizing uniform linear array configuration. By proposing an ...

A constrained squared sine derived adaptive (CSSDA) algorithm is proposed in this paper, which provides better steady-state behavior than existing algorithms in impulsive noise environments. The devised CSSDA works by constructing a squared sine ...

To harness the benefits of machine learning (ML), users often face the challenge of sharing their private data with a central entity for model training. However, data sharing can be impractical due to privacy concerns, data size, wireless resource ...

In some communication systems, the transmitted signal is contaminated by impulsive noise with a non-Gaussian distribution, which usually causes significant performance degradation to communication receivers. To deal with the impulsive noise, this ...

This paper presents a novel single feedback based kernel generalized maximum correntropy (SF-KGMC) algorithm by introducing a single delay into the framework of kernel adaptive filtering. In SF-KGMC, the history information implicitly existing in ...

As an important component of IoT-oriented applications, the indoor positioning estimation is getting increasing concern with IoT’s rapid development. However, the performance of indoor positioning is heavily relied on the complexity of the ...

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• A robust direction-of-arrival estimation method for impulsive noise environments. This algorithm is robust to the probability density function of impulsive ...

The performance of conventional direction-of-arrival (DOA) estimation methods degrades greatly when there are few snapshots and the noise model is mismatched, especially in impulsive noise environments. To solve this problem, this ...

In this paper, we present a Lorentzian-ℓ p ( 0 < p < 1 ) optimization for recovering sparse signals from measurements corrupted by two types of impulsive noise. A smoothing strategy for nonconvex ℓ p norm is employed and an efficient ...