一般的LMS算法应用参见该篇。 一般的LMS实际应用 本文设计LMS背后的数学理论知识。 1. The Least Mean Squares algorithm (LMS) SD研究的最陡下降方法是一种递归计算信号统计量已知时维纳滤波器的递归算法 (knowledge about R och p)。
This chapter develops an alternative to the method of steepest descent called the least mean squares (LMS) algorithm, which will then be applied to problems in which the second-order statistics of the signal are unknown. Due to its simplicity, the LMS algorithm is perhaps the most widely used...
The proposed two-dimensional median least mean squares (TDMLMS) algorithm is a gradient-based steepest descent algorithm and employs the sample median of the instantaneous gradients within a suitable window as a measure of the true gradient. The nonlinear action of the median filtering operation ...
AcronymDefinition SWLMS Simple Water Level Monitoring System SWLMS Simplified Wiener Least Mean Squares (algorithm) Copyright 1988-2018 AcronymFinder.com, All rights reserved. Suggest new definitionWant to thank TFD for its existence? Tell a friend about us, add a link to this page, or visit th...
Phase-unwrapping algorithm by a rounding-least-squares approach. A simple and efficient phase-unwrapping algorithm based on a rounding procedure and a global least-squares minimization is proposed. Instead of processing ... Juarez-Salazar,Rigoberto,Robledo-Sanchez,... - 《Optical Engineering》 被引...
Block Least Mean Squares Algorithm over Distributed Wireless Sensor Network In a distributed parameter estimation problem, during each sampling instant, a typical sensor node communicates its estimate either by the diffusion algori... T Panigrahi,PM Pradhan,G Panda,... - 《Journal of Computer Network...
The update in the proposed algorithm is achieved by employing the sample median of the gradient estimates at each stage of the lattice instead of the instantaneous value as in conventional GAL. Two structures are considered: the first is the normal lattice while the second incorporates an ...
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The least mean squares (LMS) algorithm is one of the most popular recursive parameter estimation methods. In its standard form it does not take into account any special characteristics that the parameterized model may have. Assuming that such model is sparse in some domain (for example, it has...