P. R. Diniz, "The Least-Mean-Square (LMS) Algorithm," in Adaptive Filtering, ed: Springer US, 2008, pp. 1-54.Paulo S.R. Diniz, "The Least-Mean-Square (LMS) Algorithm," Algorithms and Practical Implementation, 2008, Springer US, pp 1-54...
Paulo S.R. Diniz, "The Least-Mean-Square (LMS) Algorithm," Algorithms and Practical Implementation, 2008, Springer US, pp 1-54P. S. R. Diniz, "The least-mean-square ͑LMS͒ algorithm," in Adaptive Filtering: Algorithms and Practical Implementa- tion ͑Kluwer Academic, Dordrecht, ...
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The least mean square (LMS) algorithm is a type of filter used in machine learning that uses stochastic gradient descent in sophisticated ways – professionals describe it as an adaptive filter that helps to deal with signal processing in various ways. Advertisements Techopedia Explains Least Mean...
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample-by-sample update for an adaptive filter in reproducing kernel Hilbert spaces (RKHS), which is named in this paper the KLMS. Unlike the accepted view in kernel methods, this paper...
The least-mean-square (LMS) algorithm is a useful and popular procedure for adaptive signal processing of both real-valued and complex-valued signals. Past analysis of the complex LMS algorithm has assumed that the input signal vector is circularly-distributed, such that the pseudo-covariance matri...
aLMS(Least Mean Square) algorithm, based on minimum mean square error, has the advantages of simple structure, fast convergence and low computational complexity among many adaptive filtering algorithms. But along with the improvement of people's demand for communication quality, and no consideration on...
m近似的核最小均方算法(NysKLMS,kernel least mean square algorithm based on the Nystr?m method)。王文月... 王文月 - 西南大学 被引量: 0发表: 0年 Randomized, Multicenter Study to Assess the Effects of Different Doses of Sildenafil on Mortality in Adults With Pulmonary Arterial Hypertension ...
Due to its fast convergence rate, the recursive least-squares (RLS) algorithm is very popular in many applications of adaptive filtering, including system identification scenarios. However, the computational complexity of this algorithm represents a major limitation in applications that involve long filter...
In such cases, the performance of the well-known least-mean square (LMS) algorithm or that of any of its variants remains sub-optimal at best. As a remedy to this, the least-mean fourth (LMF) algorithm was later proposed but its high computational load was found to be a constraining ...