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)。 问题是,这个信息通常是未知的! LMS是一种基于与最陡下降法相同的原理的方法,但其统计量是连续估计的。 由于统计量是连续估计的,因此LMS算法可以适应信号统计量...
5)least mean square (LMS) algorithm最小均方(LMS)法 6)Least Mean Square (LMS)最小均方(LMS) 延伸阅读 最小辐亮度与最小辐照度(见核爆炸火球)最小辐亮度与最小辐照度(见核爆炸火球)minimum-brightness and minimum-irradiance zuixiao fuliangdu yu zuixiaofu乙haodu最小辐亮度与最小辐照度(minimum-bright...
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...
NLMS (Normalized Least Mean Squares) 是LMS (Least Mean Squares) 算法的一种改进。与LMS算法相比,NLMS算法具有更快的收敛速度和较小的稳态误差。NLMS算法的更新公式为: 其中, :当前时刻的权重向量。w(n):当前时刻的权重向量。 :步长因子,用于控制算法的收敛速度。μ:步长因子,用于控制算法的收敛速度。
Least Mean Squares Regression(一) 1. Examples 假设我们想从一辆汽车的重量和年龄来预测它的里程数: 我们想要的是:一个可以使用x1x1和x2x2来预测里程的function。 线性回归:利用线性模型预测连续值的策略 假设:输出是输入的线性函数 Mileage=w0+w1⋅x1+w2⋅x2Mileage=w0+w1⋅x1+w2⋅x2 学习:利用...
The Least Mean Square (LMS) algorithm, introduced by Widrow and Hoff in 1959 [12] is an adaptive algorithm, which uses a gradient-based method of steepest decent [10]. LMS algorithm uses the estimates of the gradient vector from the available data. LMS incorporates an iterative procedure that...
This paper presents channel estimation scheme based on Leaky Least Mean Square (LLMS) algorithm proposed for BPSK-QPSK-PSK MIMO OFDM System. So by designing this we are going to analyze the terms of the Minimum Mean Squares Error (MMSE), and Bit Error Rate (BER) and improve Signal to ...
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 ...
Kernel least mean square algorithm with constrained growth The linear least mean squares (LMS) algorithm has been recently extended to a reproducing kernel Hilbert space, resulting in an adaptive filter built from ... PP Pokharel,W Liu,JC Principe - 《Signal Processing》 被引量: 79发表: 2009年...
A method of operating an equalizer includes combining a Least Mean Squares (LMS) algorithm and a Least Squares (LS) algorithm to determine a set of equalizer tap values to be used in processing a signal. A channel impulse response (CIR) is computed, and an equalizer taps interval is then ...