搜索资源列表
Chaaddred
- LMS自适应算法自适应预测的计算机实验matlab仿真例子-LMS adaptive prediction algorithm for the adaptive computer simulation experiments Matlab example
Volterra_MultiStepPred_luzhenbo
- 基于Volterra滤波器混沌时间序列多步预测 作者：陆振波，海军工程大学 欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页 电子邮件：luzhenbo@sina.com 个人主页：luzhenbo.88uu.com.cn 参考文献： 1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03 2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlineariti
本自适应LSL算法实现线性预测
- 本自适应LSL算法实现线性预测 以及考察LSL算法的收敛性： 与LMS、RLS算法进行性能比较 -The LSL algorithm adaptive linear prediction and to study the LSL algorithm convergence: the LMS, RLS algorithm performance comparison
LMS111
- 应用LMS算法，用Matlab编程实现线性预测.-Application of LMS algorithm, using Matlab Programming Linear Prediction.
LMSandModelIdentificationLinearPrediction
- 自己编写的LMS基本算法以及LMS模型识别以及线性预测等.-I have written the basic LMS algorithm and LMS models, such as recognition and linear prediction.
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
LMSAdaptiveLinearPrediction
- Source Code for LMS adaptive prediction test
LMS
- 用LMS算法预报时间序列，对比真实值和预报值-LMS algorithm with time-series prediction, compared to the true value and forecast value
VolterraRls
- 应用LMS算法对Volterra级数预报，结果收敛，效果很好-Application of LMS algorithm Volterra series prediction, the results of convergence, good results
LMSAFFilter
- 在分析最小均方自适应滤波器(LMSAF)均方误差(MSE)的收敛性时，文献常用统计自相关矩阵代替瞬时自相关矩阵以简化分析，由此得出的收敛条件比较粗糙。本程序指出：不相关高斯输入情况下，无需如上简化，可依据高斯阶矩因式分解定理得到确切的MSE收敛条件，相应的失调表式能更准确地预报失调-In the analysis of LMS adaptive filter (LMSAF) the mean square error (MSE) convergence, the literature commo
LMS
- LMS prediction algorithm for noise reduction
perceptron
- lms渐进预测算法，非常好用 -lms progressive prediction algorithm, incremental prediction algorithm is very easy to use lms, very easy to use
kalmanandlms
- kalman滤波和LMS滤波MATLAB仿真和预测结果分析-kalman filter and the LMS filter MATLAB simulation and prediction results
xinhaoyuce
- 基于LMS自适应算法的信号预测，可用于图像处理，可用于语音信号处理-LMS adaptive algorithm based on signal prediction, can be used for image processing, can be used for speech signal processing
AdaptiveLinearPredictionFilter-LMS
- Advanced Digital Signal Processing Adaptive Linear Prediction Filter
LMS
- 基于一阶AR模型u(n)=0.99u(n-1)+v(n),白噪声方差0.93627.步长0.05.分别使用M=2和M=3抽头的滤波器，用LMS算法实现u(n)的线性预测估计。并附仿真图已被参考。-Based on a first-order AR model u (n) = 0.99u (n-1) the+v (n), the white noise variance 0.93627 step 0.05. Respectively with M = 2 and M = 3-tap filter,
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
adaptive filter (2)
- MATLAB codes for adaptive filtering using least mean square, nominal LMS and Wiener filter using forward linear prediction and backward linear prediction.
LMS
- LMS算法实现一阶AR模型的线性预测估计(LMS algorithm for linear prediction estimation of first order AR model)
LMS与RLS对比
- 预测信号由二阶AR模型产生，为二阶线性预测滤波器，LMS算法与RLS算法性能对比(The predicted signal is generated by the two order AR model, and is the two order linear prediction filter,performance comparison between LMS algorithm and RLS algorithm)