Witryna1 sty 2024 · The robust least mean logarithmic square (RLMLS) algorithm is proposed in Section 3. The mean square performance analysis of RLMLS is performed in Section 4. Section 5 presents the VSSRLMLS algorithm. In Section 6, Monte Carlo simulations are conducted to validate the mean square deviation (MSD) performance of the … WitrynaWidrow (1971) proposed the least mean squares (LMS) algorithm, which has been extensively applied in adaptive signal processing and adaptive control. The LMS al. …
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WitrynaThe least mean-square (LMS) is a search algorithm in which a simplification of the gradient vector computation is made possible by appropriately modifying the objective function –. The LMS algorithm, as well as others related to it, is widely used in various applications of adaptive filtering due to its computational simplicity [ 3 ]–[ 7 ]. Witryna1 sie 2016 · The Normalized Least Mean Square (NLMS) algorithm belongs to gradient class of adaptive algorithm which provides the solution to the slow convergence of the Least Mean Square (LMS) algorithm. Motivated by the recently explored q-gradient in the field of adaptive filtering, we developed here a q-gradient based NLMS algorithm. city high city high
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Witryna2 maj 2024 · Moreover, the HFBLMS scheme is introduced by combining Hierarchical Least Mean Square (HLMS) algorithm and the Fractional Calculus (FC) concept. Furthermore, the prediction process is carried out based on the developed HFQKLMS approach for data aggregation. ... This approach highly improved the lifetime of the … Witryna1 mar 2024 · In this paper, we studied the method that can improve the convergence speed of random Fourier feature-based least-mean-square algorithm. Based on the variable forgetting factor and... Witryna15 gru 2011 · Different from sparsification, the new approach uses the “redundant” data to update the coefficient of the closest center. In particular, a quantized kernel least … city high girls basketball