A filter coefficient correction term used by the equalizer filter is generated by the tap coefficients generator using a normalized least mean square (NLMS) algorithm. In another embodiment, a plurality of equalizer filters are utilized, whereby each equalizer receives a sample data stream from a ...
normalized NLMS(正规化最小均方 )外推滤波器的使用可以起到更准确地跟随动态变化的信道并因此从由可用导频提供的传递函数的样本更准确地估计信道的作用。 NLMS(Normalized Least Mean Square)外挿フィルタの使用は、動的変化チャネルを、より正確に追跡することができ、ひいては、使用可能なパイロットから...
Normalized Least Mean Square Normalized Least Means Squares Normalized Least-Squares Channel Error Normalized Levenshtein Distance Normalized Line Balance Normalized Matched Filter Normalized Maximum Likelihood Normalized Maximum Rate of Relaxation Normalized Mean Absolute Error ...
response,bydevelopinganetworkusingnormalizedleast—mean—square(LMS)adaptivefilteringalgorithm.Thecommandinputwas correctedbyweightstogeneratethedesiredinputforthealgorithm,andthefeedbackwasbroughtintothefeedbackcorrection, whoseoutputwastheweightedfeedback.TheweightsofthenormalizedLMSadaptivefilteringalgorithmwereupdatedon...
LMS算法-逻辑或运算思路代码运行结果LMS算法-二值分类思路代码运行结果LMS算法-逻辑或运算思路LMS算法全称为 least mean square 算法,中文名叫最小均方算法.在ANN领域,均方误差是指样本预测输出值与实际输出值只差的平方的期望值,记为MSE.设observed为样本真值,predicted为预测值,计算公式如下:LMS的算法策略是使均方误...
PURPOSE: A modified variable error data normalized step size least mean square adaptive filter system is provided to restore a signal in an optimal state by improving a convergence speed.;CONSTITUTION: A first filter receives an input signal. The first filter has a first filter coefficient. A se...
A Variable Step-Size Partial-Update Normalized Least Mean Square Algorithm for Second-Order Adaptive Volterra Filters Partial-update (PU) algorithms offer reduced computational complexity to adaptive second-order Volterra filters (SOV) in nonlinear systems while retaining ... K Mayyas,L Afeef - 《Cir...
I. INTRODUCTION N adaptive filtering applications for modeling, equalization, control, echo cancellation, and beamforming, the widely used least-mean-square(LMS) algorithm has proven to be both a robust and easily-implementedmethod for on-line estimation of time-varying system parameters. The LMS ...
As a classical augmented complex-valued adaptive algorithm, the augmented complex-valued least mean square (ACLMS) algorithm can obtain the optimal estimate in the sense of minimum mean square error (MMSE) under Gaussian noise assumption and non-circular inputs [11]. In [8], the authors ...
A new filter-x least mean square adaptive algorithm and its sign error edition are proposed. The proposed algorithms use a self-normalization method that combines self-normalization and p-norm based on the presented algorithms. The self-p-normalization method reuses the filtered reference signal to...