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)。
Recently, a Least-Mean Squares (LMS) algorithm was developed for computing the optimum weight vector of the adaptive linear filter applied in the FrFT domain to estimate a SOI from the environment. A computational complexity exists, however, in that typically the FrFT rotational parameter `a' ...
In this paper we build practical (computable) error bound analysis of the stochastic gradient algorithm when the loss function is time-dependent and quadratic in the parameters, as arising from standard linear regression model. The long term goal is to address this problem in general nonlinear ...
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 ...
An Improved Adaptive Normalized Least Mean Square Filtering Algorithm for On-Line Monitoring of Transformer Partial Discharge It is significant for secure and stable operation of high-capacity power transformers to carry out on-line monitoring of partial discharge (PD) and the key... YF Lei,GC Yan...
The enhanced normalized Fry (ENFry) method automates ellipse fitting by entering center-to-center distances between these "touching" objects into the least-squares ellipse algorithm. For homogeneously deformed populations of 200 objects, the ENFry method gives an accurate and precise measure of whole...
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...
T. J. Moir, "Loop-Shaping Techniques Applied to the Least-Mean-Squares Algorithm," Signal, Image and Video Processing, Vol. 5, 2011, pp. 231-243. http://dx.doi.org/10.1007/s11760-010-0157-9T. J. Moir, “Loop-Shaping Techniques Applied to the Least-Mean-Squares Algorithm,” Signal...
Finally, it is shown that the latter can be derived from the proposed algorithm.Lakkis, I.McLernon, D.Iee Proceedings Part KLakkis, I., McLernon, D.: Least mean squares algorithm for frac- tionally spaced blind channel estimation. IEE Proc. Vis. Image Signal Process. 146(4), 181-...
Our main result is the first algorithm that returns such an $\\\epsilon$-coreset using finite and constant memory during the streaming, i.e., independent of $n$, the number of rows seen so far. The coreset consists of $O(d \\\log ^{2}\\\;d / \\\epsilon ^{2})$ weighted...