文件名称:SVDTLS
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用Matlab仿真实现最小二乘法和总体最小二乘法估计
假设仿真的观测数据 产生，其中 为0均值， 单位方差的高斯白噪声，取n=1,2,....128。
试用TLS，取AR阶数为4，估计AR参数 和正弦波频率；再用SVD-TLS ，估计AR参数 和正弦波频率。
(1)、在仿真中，AR阶数取为4和6。
(2)、执行SVD-TCS时，AR未知。仿真运行至少二十次。
-Simulation using Matlab and the overall least squares least squares estimate assumptions simulated observation data are generated, where 0 mean, unit variance Gaussian white noise, take n = 1,2 ,.... 128. Try TLS, take AR order of 4, estimated AR parameters and the sine wave frequency then SVD-TLS, estimated AR parameters and the sine wave frequency. (1), in the simulation, AR order is taken as 4 and 6. (2), when the implementation of SVD-TCS, AR is unknown. Simulation run at least twenty times.
假设仿真的观测数据 产生，其中 为0均值， 单位方差的高斯白噪声，取n=1,2,....128。
试用TLS，取AR阶数为4，估计AR参数 和正弦波频率；再用SVD-TLS ，估计AR参数 和正弦波频率。
(1)、在仿真中，AR阶数取为4和6。
(2)、执行SVD-TCS时，AR未知。仿真运行至少二十次。
-Simulation using Matlab and the overall least squares least squares estimate assumptions simulated observation data are generated, where 0 mean, unit variance Gaussian white noise, take n = 1,2 ,.... 128. Try TLS, take AR order of 4, estimated AR parameters and the sine wave frequency then SVD-TLS, estimated AR parameters and the sine wave frequency. (1), in the simulation, AR order is taken as 4 and 6. (2), when the implementation of SVD-TCS, AR is unknown. Simulation run at least twenty times.
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SVDTLS.m
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