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Fast LMS-Newton algorithms based on autoregressive
- 一种利用LMS的回声抑制的实现方法，经典文献-echo suppression of the method, classic literature
newblms
- 分块BLMS 算法,首先将信号分成若干小快，然后进行LMS计算，解决了计算工程量大的问题-Block BLMS algorithm, first of all, the signal is divided into several small fast, and then proceed to LMS, the solution to calculate the engineering problem of a large quantity of
LMS
- 采用一种快速收敛变步长LMS（Least mean square ） 自适应最小均方算法matlab源程序，其中算法所做的工作是用FIR 滤波器的预测系统，对IIR系统进行预测，如果阶数越高越能逼近被预测系统。-Using a fast convergence of variable step size LMS (Least mean square) adaptive least mean square algorithm matlab source, one of algorithm is t
lms
- lms算法是自适应中的一种简单，易于实现的方法，收敛速度很快，所以应用很多-lms algorithm is adaptive in a simple, easy to implement method of fast convergence, so the application of many
adaptive_algorithm
- 包含常用的LMS，RLS，快速RLS（FTF）等自适应滤波算法，搜集了多种合集，全部为m文件，很有启发，更好理解自适应算法。-Contains the commonly used LMS, RLS, fast RLS (FTF) adaptive filtering algorithm, etc. to collect a wide range of Collection, all for the m file, very enlightening and better understandin
BLMS
- 自适应滤波的块型最小均方差算法（B-LMS）,能够快速跟踪过程的变化-Block adaptive filtering algorithm based on LMS (B-LMS), to fast track the process of change
LMS
- 在一种变步长算法基础上, 从语音信号相关性的角度出发, 提出了一种新的去相关变步长LMS 算法( DCL—NLMS) 。该算 法结构简单, 收敛速度快, 稳态失调小, 计算量与NLMS 算法相当。仿真结果表明, 该算法在处理强相关性信号时, 不仅收敛速度明 显快于其余算法, 而且稳态失调特性也有很大优势-Based on the variable step NLMS arithmetic, this paper proposes a new uncorrelated variable s
LMS-algorithm2
- 格-梯型结构的LMS算法，按照最小均方准则，设计出阶数和时间分别递推的自适应滤波器，可以进行梯型滤波，又具有格型预测前后节独立、收敛快速的优点，但计算量大。-Grid- LMS algorithm in a ladder-type structure, in accordance with the minimum mean square criterion, design order and time adaptive recursive filter, ladder filter, and l
223-05545653
- IEEE(2010) paper on Fast Convergent LMS Adaptive Receiver for MC-CDMA Systems with Space-Time Block Coding
lms
- Adaptive filtering algorithm based on LMS (B-LMS), to fast track the process of change in channel between transmitter & receiver
fastlms
- 快速块LMS算法 利用FFT，实现频域的LMS快速算法，并且能够加快算法的收敛速度-Fast Block Least Mean Squares
qpsk_fast_dfe_2009_06_26
- fast transform domain normalized leaky LMS DFE example model. matlab. simulink.
RLS_ALGORITHM
- The Recursive least squares (RLS) is an adaptive filter which recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This is in contrast to other algorithms such as the least mean
111186758csLMS
- 这是一种改进的最小均方算法，算法具有较快的收敛速度和较低的稳态误差，计算简单。(This is an improved minimum mean square algorithm. The algorithm has fast convergence speed and low steady-state error, and the calculation is simple.)
LRS
- RLS 递归最小二乘滤波器算法！！！！！！！！！！！！！！！！！！！！！(Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in