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matlab
- 自适应的最小均方算法：只要自适应线性组合器每次迭代运算时都知道输入信号和参考响应，选用LMS算法很合适。-Adaptive least mean square (LMS) algorithm: as long as the adaptive linear combiner for each iteration when they know that the input signal and reference response, selection of LMS algorithm is ver
LMS_RLS
- 拟使用基于LMS与RLS的自适应算法在MATLAB平台上对带有两个权的自适应线性组合器进行仿真,进而对两类算法的性能作比较，同时也考察了两种算法在不同参数条件下曲线收敛性的变化-Intending to use the LMS and RLS-based adaptive algorithm in the MATLAB platform with two pairs of the right to self-adaptive linear combiner is simulated, and t
RLSxiebojiance
- 以自适应线性组合器为时变谐波检测器的模型, 根据逆归最小乘自适应滤波算法较好的跟踪性能, 使之应用于时变谐波的跟踪检测。仿真表明该方法比以往的基于最小均方 自适应滤波算法的谐波幅值和相位参数的测定具有更好的跟踪效果。-Adaptive linear combiner with harmonic detector is too variable model, according to inverse normalized least square adaptive filter algorit
my_new_lms
- LMS算法是一种很有用且很简单的估计梯度的方法。这种算法60年代初得出以后很快得到应用，它的突出优点是计算量小易于实现，且不要求脱线计算。只要自适应线性组合器每交迭代运算时都知道输入信号台和参考响应，那么，选用LMS算法是很合适的。-LMS algorithm is a very useful and very simple estimate of the gradient method. The algorithm reached 60 soon after the early applied
LMS
- matlab程序，已验证。里面是信号处理中LMS算法的具体实例，并附有详细的解释说明。实例是针对文档中的权值线性组合器，并画出了LMS算法性能曲面等值线-There are specific examples of signal processing LMS algorithm, together with a detailed explanation. There are specific examples of signal processing LMS algorithm, togethe