Geometric algebra based least mean m-estimate robust adaptive filtering algorithm and its transient performance analysis

Lv, Shaohui; Zhao, Haiquan; He, Xiaoqiong

doi:10.1016/j.sigpro.2021.108235

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…The methods that are resistant to their occurrence are used to prevent this, to compensate for the observations suspected of gross errors. These methods belong to the class of strong estimation (M-estimation) [14,26]. They allow to eliminate the influence of outliers on the process of equalization and thus obtain more accurate results [27].…”

Section: Numerical Processing Of Measurement Resultsmentioning

confidence: 99%

Accuracy Characteristics of the Selected Diagnostics Methods and the Adjustment of Geodetic Observations

Kulupa

Magda

Mrówczyńska

2021

Civil and Environmental Engineering Reports

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The article presents the results of the adjustment of the experimental horizontal geodetic network using the classical method and the estimation of strengths in identifying observations with gross error and analyzing the accuracy of the obtained results. The presented analyses were made considering the possibility of their use in implementation networks and measurement and control networks used for monitoring building structures. The paper’s subject was a horizontal network established on the Morasko campus (Poznań). While creating it, the practical needs and economics of measurements were taken into account. The obtained results of numerical analyzes confirmed the benefits of using the methods of estimating strengths in the equalization process, which give satisfactory results in the case of outliers.

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Section: Numerical Processing Of Measurement Resultsmentioning

confidence: 99%

Accuracy Characteristics of the Selected Diagnostics Methods and the Adjustment of Geodetic Observations

Kulupa

Magda

Mrówczyńska

2021

Civil and Environmental Engineering Reports

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“…In Lv et al, 225 the transient performance of the GA least mean M‐estimate (GA‐LMM) filtering is analyzed. Further, the variable step‐size variant VSS‐GA‐LMM is designed to eliminate the constraint of constant step size on the performance of the GA‐LMM, and the optimal step size is obtained by maximizing the difference of mean square deviation (MSD) between successive iterations, effectively balancing the contradiction between convergence rate and steady‐state error.…”

Section: Signal Image and Video Processingmentioning

confidence: 99%

Current survey of Clifford geometric algebra applications

Hitzer

Hildenbrand

2022

Math Methods in App Sciences

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“…IGITAL signal processing has been developed for many years, and since the classical least mean squares (LMS) algorithm [1] was proposed, adaptive filtering algorithms are extensively available for the fields of system identification, echo cancellation, and frequency estimation for power systems [2][3] [4]. In fact, the input signal often contains noise as well, due to personnel errors, sensor defects, and other problems.…”

Section: Introductionmentioning

confidence: 99%

Robust Maximum Correntropy Criterion Subband Adaptive Filter Algorithm for Impulsive Noise and Noisy Input

Zhao

2022

IEEE Trans. Circuits Syst. II

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Although the known maximum total generalized correntropy (MTGC) and generalized maximum blakezisserman total correntropy (GMBZTC) algorithms can maintain good performance under the errors-in-variables (EIV) model disrupted by generalized Gaussian noise, their requirement for manual adjustment of parameters is excessive, greatly increasing the practical difficulty of use. To solve this problem, the total arctangent based on logical distance metric (TACLDM) algorithm is proposed by utilizing the advantage of few parameters in logical distance metric (LDM) theory and the convergence behavior is improved by the arctangent function. Compared with other competing algorithms, the TACLDM algorithm not only has fewer parameters, but also has better robustness to generalized Gaussian noise and significantly reduces the steady-state error. Furthermore, the analysis of the algorithm in the generalized Gaussian noise environment is analyzed in detail in this paper. Finally, computer simulations demonstrate the outstanding performance of the TACLDM algorithm and the rigorous theoretical deduction in this paper.

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Geometric algebra based least mean m-estimate robust adaptive filtering algorithm and its transient performance analysis

Cited by 4 publications

References 11 publications

Accuracy Characteristics of the Selected Diagnostics Methods and the Adjustment of Geodetic Observations

Accuracy Characteristics of the Selected Diagnostics Methods and the Adjustment of Geodetic Observations

Current survey of Clifford geometric algebra applications

Robust Maximum Correntropy Criterion Subband Adaptive Filter Algorithm for Impulsive Noise and Noisy Input

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