AR-model-with-rls-and-lms
代码说明：
代码实现了二阶AR模型的最优权值递推，使用了LMS和RLS两种方法，对二者性能进行了比较，分别进行了单次和100次平均进行性能观察，并且仿真了不同步长因子对LMS算法的影响以及不同lamda值对RLS算法的影响。文档包含了模型的详细介绍以及2种方法的理论仿真和结果分析。代码以附在之后。(Code to achieve the optimum weights recursive second order AR model, the use of LMS and RLS are two methods were compared for the two properties, were observed and 100 times the average per-performance and simulated sync Effect of a growth factor RLS algorithm impact on LMS algorithm and different lamda value. Document contains the results of theoretical simulation and detailed description of the model and two methods of analysis. Code annexed.)
文件列表：
AR model with rls and lms.docx,580146,2015-05-18
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