Convergence Issues in Sequential Partial-Update LMS for Cyclostationary White Gaussian Input Signals

Wang, Wenyuan; Doğançay, Kutluyıl

doi:10.1109/lsp.2021.3074089

Cited by 9 publications

(5 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, we will broadly categorized partialupdating adaptive algorithms into two classes based on different updating strategies as follows: first, various kinds of using certain data-dependent selection criteria adaptive algorithms were proposed to update the tap-weights, including the selective-block-update NLMS (SBU-NLMS) algorithm [16], the M-max NLMS algorithm (Max-NLMS) [17], the set-membership PU-NLMS algorithm [18]and its improved version, the L-norm-based algorithm [19]. ese algorithms generally use the characteristics of unfixed updating strategies to achieve a faster convergence rate, like the BS-LMS and GZA-LMS.…”

Section: Introductionmentioning

confidence: 99%

Selective Partial Update Adaptive Filtering Algorithms for Block-Sparse System Identification

Wei

2022

Security and Communication Networks

View full text Add to dashboard Cite

The block-sparse normalized least mean square (BS-NLMS) algorithm which takes advantage of sparsity, successfully shows fast convergence in adaptive block-sparse system identification, adaptive control, and other industrial informatics applications. It is also attractive in acoustic processing where long impulse response, highly correlated and sparse echo path are encountered. However, the major drawback of BS-NLMS is largely computational complexity. This paper proposes a novel selective partial-update block-sparse normalized least mean square (SPU-BS-NLMS) algorithm. Compared with conventional BS-NLMS for block-sparse system identification, the proposed elective partial-update block-sparse NLMS algorithm takes partial-update blocks scheme which is determined by the smallest squared Euclidean-norm at each iteration instead of entire block coefficients to save computations. Computational complexity analysis is conducted to help researchers select appropriate parameters for practical realizations and applications. Computer simulations on acoustic echo cancellation are conducted to verify the results and the effectiveness of the proposed algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Selective Partial Update Adaptive Filtering Algorithms for Block-Sparse System Identification

Wei

2022

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…The weight coefficient experiences a relatively large jump when the interference frequency changes. In addition, even if the weight coefficients jump, the adaptive filter will quickly make the weight coefficients converge [43,44]. In the context of this experiment, the convergence time is about 2us.…”

Section: Time-domain Anti-jamming Methods For Sweeping-frequency Inte...mentioning

confidence: 99%

Influence of sweep interference on satellite navigation time-domain anti-jamming

Qiao

et al. 2023

Front. Phys.

View full text Add to dashboard Cite

The global navigation satellite system (GNSS), represented by global positioning systems (GPS), is widely used in various civil and military fields and represents an essential basis for space-time information services. However, the radar signals partially overlap with the frequency band of satellite navigation signals, seriously affecting the normal reception of weak satellite navigation signal power. To further improve anti-jamming with sweep interference in the time domain, this paper focuses on the sweep interference scenario, studies the influence of the sweep interference on time-domain-adaptive anti-jamming, and proposes a timing reset based on the adaptive filter. The proposed method can effectively deal with the influence of sweep interference on time-domain-adaptive anti-jamming and can suppress interference and protect signals at the same time. Simulation experiments verify the effectiveness of the anti-jamming method proposed in this paper. Under the typical simulation scenarios, the influence time of the frequency sweep interference on the navigation signal is less than 1 m when the timing reset period is 1 m, which is significantly reduced compared to traditional methods. The proposed anti-jamming method is of great significance for improving the survivability of satellite navigation receivers in sweep interference scenarios.

show abstract

“…, 𝛾 and 𝛼 are constants. For ease of analysis, we state the following assumptions, which are common in analysis of the performance of the adaptive filter 30,31 Assumption 1. At the steady state, the vector w s,i approaches the optimal vector w o s , and…”

Section: Analysis Modelmentioning

confidence: 99%

“…For ease of analysis, we state the following assumptions, which are common in analysis of the performance of the adaptive filter 30,31 …”

Section: Steady‐state Analysismentioning

confidence: 99%

A robust adaptive decomposable Volterra filter based on the hyperbolic tangent Leclerc function and its performance analysis

Liu,

Li,

2024

Adaptive Control & Signal

View full text Add to dashboard Cite

SummaryMost of the existing adaptive filter algorithms pay more attention to improving performance while ignoring the computational complexity and the impact of the impulsive environment. When encountering the impulsive noise environments, the performance of traditional nonlinear adaptive filter may be significantly reduced and usually needs high computational cost. Therefore, this article proposes a hyperbolic tangent Leclerc robust nonlinear adaptive filter based on the low complexity decomposable Volterra model (HTLNAF‐DVM). The filter is implemented by imposing a rank‐one structure on the full Volterra model to get a product of linear filters, and employs a hyperbolic tangent Leclerc function as a robust norm to effectively improve the robustness against the impulsive noise. In addition, we give the theoretical analyses of the steady‐state mean‐square performance of the proposed HTLNAF‐DVM. Finally, the simulation results prove that the proposed HTLNAF‐DVM algorithm has better performance than the existing algorithms and fit well with the theory.

show abstract

Convergence Issues in Sequential Partial-Update LMS for Cyclostationary White Gaussian Input Signals

Cited by 9 publications

References 38 publications

Selective Partial Update Adaptive Filtering Algorithms for Block-Sparse System Identification

Selective Partial Update Adaptive Filtering Algorithms for Block-Sparse System Identification

Influence of sweep interference on satellite navigation time-domain anti-jamming

A robust adaptive decomposable Volterra filter based on the hyperbolic tangent Leclerc function and its performance analysis

Contact Info

Product

Resources

About