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mathworks
- 基于最小二乘法和最小均方误差法的信道估计，包括详细的仿真结果，如误码率和均方误差。-Based on the least squares and minimum mean square error of channel estimation methods, including detailed simulation results, such as error rate and MSE.
channelestmation
- 本程序比较了LS(最小二乘）和最小均方误差准侧下OFDM信道估计的误码率，给出了LS及MESE实现的源程序，是信道估计初学者的理想参考资料-This procedure compares the LS (least squares) and minimum mean square error of quasi-lateral channel estimation of OFDM bit error rate, given the realization of the LS and the MES
TLSesprit
- 总体最小二乘法的ESPRIT方法，这种算法的估计精度明显好于原来的ESPRIT算法。可以很好的估计出信号的角度。仿真中用的是均匀阵列。-Total least squares method of the ESPRIT method, the algorithm of the estimation accuracy significantly better than the original ESPRIT algorithm. Can be a very good signal to estima
SVD_TLS
- 使用自编函数基于奇异值分解总体最小二乘法（svd-tls）实现AR模型谱估计 -The use of self-functions in general based on singular value decomposition least square method (svd-tls) to achieve AR model spectrum estimation
stateestimation
- 状态估计优秀硕士论文，提出了一种基于分块雅可比矩阵的加权最小二乘估计算法；提出了潮流岛状态变量的概念，用潮流岛的状态变量代替岛内所有节点的状态变量-State estimation for outstanding master
lubangxingdetuxiangpinjie
- 图像拼接的核心是图像的配准.提出一种准确、高效的图像拼接方法:利用Harris角点检测算子提取相邻图 像的特征点,通过Euclid度量改进熵变换的算法,进行特征点匹配,并通过最小均值二乘估计求解相邻图像的变换 矩阵,以此实现宽视角图像的拼接.实验结果表明:所给出的算法能够实现场景图像的精确匹配. -Image mosaic is the core of image registration. Make an accurate and efficient method of image
m12_3
- 为了改善噪声e(k)为有色噪声模型的系统参数估计的统计特性，提出了一种增广矩阵的方法，称为增广最小二乘算法，MATLAB实现范例-In order to improve the noise e (k) for the colored noise model of the system parameters estimated statistical characteristics, an Augmented Matrix method, called Augmented Least Square
LMS
- 简单的最小二乘逼近算法，用于系统辨识，方便修改噪声参数和系统参数，为系统辨识和仿真作业的源代码。-Simple least-squares approximation algorithm for system identification to facilitate the modification of system parameters and noise parameters for the system identification and simulation of the sourc
ModelIdentification
- 关于模型辨识的MATLAB仿真源码。有使用最小二乘的建模，有极大似然估计建模的方法。每个重点例句都有详细的解释。-On the MATLAB simulation model of source identification. Modeling the use of least squares, and maximum likelihood estimation method of modeling. Each key has a detailed explanation of examples
LSM
- 递推最小二乘法估计的实现方法，很简单，有需要的就下吧-Recursive least squares estimation method is very simple, there is a need for it on the next
forgettingfactor
- 用VB编写的参数估计带遗忘因子递推最小二乘法仿真（RLS）-VB prepared using the parameters estimated with forgetting factor recursive least squares method Simulation (RLS)
CLAPACK3-Windows
- LAPACK是用Fortran90和规定套路解决系统同步线性方程组，最小二乘解线性方程组，特征值问题，以及奇异值问题。相关的矩阵分解（陆，乔莱斯基，快速反应，分解，舒尔，广义Schur ）也提供了，因为有关的计算，如重新安排的舒尔分解和估计条件号码。致密带状矩阵的处理，而不是一般稀疏矩阵。在所有领域，类似的功能是提供真正的和复杂的矩阵，在单，双精度-LAPACK is written in Fortran90 and provides routines for solving systems o
AutomatedNegotiatioDecisionModelasedonMachineLearn
- 模型利用协商历史中隐含的信息自动对数据进行标注以形成训练样本，用最小二乘支持向量回 归机学习此样本得到对手效用函数的估计，然后结合自己和对手的效用函数构成一个约束优化问题，用遗传算法求 解此优化问题，得到的最优解就是己方的反建议．实验结果表明，在信息保密和没有先验知识的条件下，此模型仍然 表现出较高的效率和效用-The proposed model labels the negotiation history data automatically by making full use
PLS1_sina
- 用于单变量的偏最小二乘回归，直接给出回归系数。 X0是自变量矩阵，Y0是因变量向量，PRESS是去除其中某一个样本而回归出的方程对 缺失样本的误差估计，SS则是使用全部样本回归出的方程对同一个样本的误差估计。 在h个成分时，计算PRESS_h与SS_h-1，若1-PRESS/SS大于0.0975时，应增加成份。 [row,col]=size(pz) -For single-variable partial least squares regression, regression
niu
- 利用AR模型进行时间序列预测的程序源代码，使用最小二乘估计法进行参数估计。拟合效果非常好。-use AR model for time series prediction of the source code, the use of least squares estimation method to estimate parameters. Fitting very good results.
Least squares identification
- 对四阶系统的最小二乘辨识； 其根本思想能表现为新的估计值 是在老的估计值 的基础上修正而得的(Least squares identification of fourth order system; Its fundamental idea can be expressed as a new estimate is based on the old estimate based on the revised)
自适应控制（有突变无阶次辨识）
- 带遗忘因子的递推最小二乘参数估计以及带有辅助变量的广义最小方差自校正控制算法及结果，源码可找我要(Recursive Least Squares Parameter Estimation with Forgetting Factor and Generalized Minimum Variance Self-Tuning Control Algorithm with Auxiliary Variables and Results)
程序代码WLS
- 加权最小二乘电网状态估计1111113gfvcndnfghhgk(Weighted least squares power system state estimation 1111113gfvcndnfghhgk)
非线性最小二乘问题
- 以误差的平方和最小为准则来估计非线性静态模型参数的一种参数估计方法。设非线性系统的模型，常用于传感器参数设定。(A parameter estimation method for estimating nonlinear static model parameters based on the minimum sum of squared errors. A model of a nonlinear system is often used for sensor parameter settin
电力系统状态估计
- 基于加权最小二乘算法和快速分解法的电力系统状态估计程序(Power system state estimation program based on weighted least square algorithm and fast decomposition method)