文件名称:Volterrra_luzhenbo4
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更新部分
1、自适应算法采用参考文献[2]的NLMS算法，收敛速度更快，所需训练次数更少。
2、自适应收敛步长在(0,2)之间存在较优取值，Lorenz序列为0.6。-update an adaptive algorithm reference [2] NLMS algorithm, convergence faster, less the number of required training. 2, adaptive step in the convergence of (0,2) between the optimum value, Lorenz sequence of 0.6.
1、自适应算法采用参考文献[2]的NLMS算法，收敛速度更快，所需训练次数更少。
2、自适应收敛步长在(0,2)之间存在较优取值，Lorenz序列为0.6。-update an adaptive algorithm reference [2] NLMS algorithm, convergence faster, less the number of required training. 2, adaptive step in the convergence of (0,2) between the optimum value, Lorenz sequence of 0.6.
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下载文件列表
Volterrra_luzhenbo4/original_test.m
Volterrra_luzhenbo4/PhaSpaRecon.m
Volterrra_luzhenbo4/LorenzData.dll
Volterrra_luzhenbo4/normalize_1.m
Volterrra_luzhenbo4/TrainTestSample_2.m
Volterrra_luzhenbo4/文件夹说明.txt
Volterrra_luzhenbo4/orginal_main.m
Volterrra_luzhenbo4/original_train.m
Volterrra_luzhenbo4/FIR_NLMS.dll
Volterrra_luzhenbo4/PhaSpa2VoltCoef.dll
Volterrra_luzhenbo4
www.dssz.com.txt
Volterrra_luzhenbo4/PhaSpaRecon.m
Volterrra_luzhenbo4/LorenzData.dll
Volterrra_luzhenbo4/normalize_1.m
Volterrra_luzhenbo4/TrainTestSample_2.m
Volterrra_luzhenbo4/文件夹说明.txt
Volterrra_luzhenbo4/orginal_main.m
Volterrra_luzhenbo4/original_train.m
Volterrra_luzhenbo4/FIR_NLMS.dll
Volterrra_luzhenbo4/PhaSpa2VoltCoef.dll
Volterrra_luzhenbo4
www.dssz.com.txt
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