搜索资源列表
RLSKF
- 递推最小二乘拟合算法 用于实时拟合时间序列ARMA模型参数 例如 陀螺仪随机噪声 股票 交通等模型的参数拟合(Recursive least square fitting algorithm is used to fit the parameters of time series ARMA model, such as gyroscope, random noise, stock traffic and so on)
LMS_RLS
- lms与rls算法比较,MATLAB 程序仿真，比较两种自适应滤波算法。最小均方(LMS)、递归最小二乘(RLS)(LMS and RLS algorithm comparison, MATLAB program simulation, comparison of two adaptive filtering algorithm. Least mean square (LMS) and recursive least squares (RLS))
MATLAB优化算法案例分析与应用《进阶篇》
- 贝叶斯分类器 基于背景差分的运动目标检测 基于小波变换的图像压缩 基于BP的模型优化预测 基于RLS算法的数据预测 等等(Bias classifier is based on background difference moving object detection, wavelet based image compression, BP based model optimization prediction, RLS based algorithm for data predicti
RLS
- MATLAB关于最小二乘法和递推最小二乘法程序(MATLAB on the least squares method and recursive least squares procedures)
递推最小二乘法实现及推广
- 最小二乘递归算法仿真及其推广应用，很好地实现了最小二乘法(Least square recursive algorithm simulation and its popularization and application, the least square method is well realized.)
rls
- simulink的递推最小二乘法用s文件编译的(The recursive least square method of Simulink is compiled with s file)
1
- FLMS Kalman RLS adaptive LMS
Desktop
- 数字预失真中matlab中LMS和RLS算法(LMS and RLS algorithms for MATLAB in digital predistortion)
1RLS_SC_RC
- 递推最小二乘法，最简单的递推最小二乘法程序(Recursive least squares method, the simplest recursive least squares procedure.)
源代码
- 基于lms的自适应滤波器仿真设计,已测试可用(Simulation design of adaptive filter based on LMS)
MVDR和RLS实现了单波束形成
- 数字波束形成器是全数字化超声成像的基础,也是高性能彩超的保证。(digital Beamforming Forming)
可变遗忘因子
- 本程序为遗忘因子最小二乘法，可以拷贝至matlab的M文件中适应(Matlab for ] least square method)
RLS系统辨识
- 包含各种最小二乘法系统辨识程序，效果较好，可以用来辨识系统(System Identification Programs Containing Various Least Square Methods)
RLS_Libattery
- 基于递归最小二乘算法在线辨识锂离子电池一阶模型参数。(The first order model parameters of lithium ion battery are identified online based on recursive least square algorithm.)
adaptive filters part2
- 自适应滤波器相关的matlab程序，包含LMS，RLS算法等的实现。由于太大了，所以该资源分为part1和part2两部分。此部分为part2！(matlab codes related to adaptive filters, including LMS and RLS algorithm, etc. the resource is divided to two parts (part1 + part2) cuz it is oversized.)
RLS-TD(lamda)
- Efficient reinforcement learning using recursive least-squares methods. Jounral of AI Research, 2002, 16, 259-292