搜索资源列表
tituiminTWOmul
- 递推广义最小二乘法,主要应用于系统辨识,按照给定的递推方程辨识参数
zuiyouhuashiyanbaogao
- 用MATLAB求解无约束的问题,主要有最速下降法,牛顿法,共轭梯度法,变尺度法(DFP和BFGS法),非线性最小二乘法。 用MATLAB求解有约束的问题,主要是外惩罚函数和广义乘子法。 以及一些对具体问题的分析,MATLAB的代码在文档里都有。 -Using MATLAB to solve the problem of non-binding, there are the steepest descent method, Newton method, conjugate gradie
GLS
- 广义最小二乘法一次完成法程序,输入为M序列信号-A complete method of generalized least squares procedure for the M series signal input
MP_DOA
- 针对多径效应的影响,提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号,采用单样本数信号矢量构造了一个前后向矩阵束,并利用两个酉矩阵对该矩阵束进行降维处理,最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵,可在低 信噪比和单样本数情况下,有效地克服多径效应,实现同时多目标低仰角估计,相比最大似然算法,避免了谱峰搜索,计算量小。仿真结果验证了该算法的有效性。-To overcome the multipath e
ren_GPC-PID
- 广义预测控制算法仿真,通过最小二乘法对系统进行在线辨识,并与PID对比,能运行的-Generalized predictive control algorithm simulation, through the of least squares method for on-line identification system, can run
LS1
- 系统辨识最小二乘法估计,递推最小二乘法估计,辅助变量法估计,广义最小二乘法估计等-System identification least squares estimation, recursive least squares estimation, instrumental variable method estimated generalized least squares estimation
matlab
- 递推最小二乘法与广义最小二乘法matlab源程序-Recursive least squares and generalized least squares matlab source program
jingmou_v42
- 时间序列数据分析中的梅林变换工具,采用偏最小二乘法,gmcalab 快速广义的形态分量分析。- Time series data analysis Mellin transform tool, Partial least squares method, gmcalab fast generalized form component analysis.
fuifie_v27
- 是本科毕设的题目,包括广义互相关函数GCC时延估计,利用最小二乘法进行拟合多元非线性方程。- The title of the commercial is undergraduate course you Including the generalized cross-correlation function GCC time delay estimation, Multivariate least squares fitting method of nonlinear equations.
fangteng
- 包括广义互相关函数GCC时延估计,高斯白噪声的生成程序,包括最小二乘法、SVM、神经网络、1_k近邻法。- Including the generalized cross-correlation function GCC time delay estimation, Gaussian white noise generator, Including the least squares method, the SVM, neural networks, 1 _k neighbor method.
loutun_v79
- 已经调试成功.内含m文件,可直接运行,包括最小二乘法、SVM、神经网络、1_k近邻法,包括广义互相关函数GCC时延估计。- Has been successful debugging. M contains files can be directly run, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Including the generalized cross-cor
Classifiers
- 我们需要成百上千的分类器来解决现实世界的分类吗 我们评估179分类17种分类器(判别分析,贝叶斯,神经网络,支持向量机,决策树,基于规则的分类器,升压、装袋、堆放、随机森林和其他合奏,广义线性模型,线性,偏最小二乘法和主成分回归,logistic回归、多项式回归、多元自适应回归样条等方法),实现在WEKA,R(有或没有插入包),C和Matlab,包括所有目前可用的相关分类。(Do-we-Need-Hundreds-of-Classifiers-to-Solve-Real-World-Class