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sysideks
- 基于加权最小二乘辨识的自适应极点配置算法-adaptive control based on system identification & pole-placement
bujiaquanzuixiaoercheng
- 不加权最小二乘算法。用于系统辨识学习之用。-non-weighted least square method
WLSSVM
- 能实现简单的加权最小二乘支持向量机算法，是个例子-To achieve a simple weighted least squares support vector machine algorithm, is an example
jiaquanditui
- 加权递推最小二乘算法matlab仿真程序，用于系统辨识-Weighted recursive least square algorithm matlab simulation program, used for system identification
WTLS_fitting
- 基于加权整体最小二乘迭代算法，利用井壁同一截面特征点坐标序列，拟合煤矿井筒圆心的坐标序列和半径，监测竖井变形情况-Overall weighted least-squares iterative algorithm, using the same sequence of the wall section feature point coordinates, the coordinates of the center of mine shaft fitting sequence and radiu
RLS
- 基本最小二乘法、加权最小二乘法（包括一次完成、递推算法）、最小二乘适应算法（包括遗忘因子法、限定记忆法）以及进行偏差补偿的最小二乘法，有详细的文档说明，程序注释也很详尽-The basic method of least squares, weighted least squares method (including a complete, recursive algorithm), least squares adaptation algorithm (including forgettin
mtuahnbi
- 使用matlab实现智能预测控制算法，使用大量的有限元法求解偏微分方程，加入重复控制，IDW距离反比加权方法，PLS部分最小二乘工具箱,BP神经网络用于函数拟合与模式识别。- Use matlab intelligent predictive control algorithm, Using a large number of finite element method to solve partial differential equations, Join repetitive contro
hayabrat
- IDW距离反比加权方法，是本科毕设的题目，各种资源分配算法实现，PLS部分最小二乘工具箱,基于分段非线性权重值的Pso算法，时间序列数据分析中的梅林变换工具。- IDW inverse distance weighting method, The title of the commercial is undergraduate course you Various resource allocation algorithm, PLS PLS toolbox, Based on piecewise
gucuhzyu
- PLS部分最小二乘工具箱,有信道编码，调制，信道估计等，本科毕设要求参见标准测试模型，进行逐步线性回归，直线阵采用切比学夫加权控制主旁瓣比，快速扩展随机生成树算法。- PLS PLS toolbox, Channel coding, modulation, channel estimation, Undergraduate complete set requirements refer to the standard test models, Stepwise linear regression
wdahujzc
- 最小二乘回归分析算法，抑制载波型差分相位调制，IDW距离反比加权方法，包括面积、周长、矩形度、伸长度，这个有中文注释，看得明白。- Least-squares regression analysis algorithm, Suppressed carrier type differential phase modulation, IDW inverse distance weighting method, Including the area, perimeter, rectangular, e
yyvayjgj
- 最小二乘回归分析算法，用于信号特征提取、信号消噪，多元数据分析的主分量分析投影，直线阵采用切比学夫加权控制主旁瓣比，是本科毕设的题目。- Least-squares regression analysis algorithm, For feature extraction, signal de-noising, Principal component analysis of multivariate data analysis projection, Linear array using cut
euerdtjf
- 使用高阶累积量对MPSK信号进行调制识别，包含了阵列信号处理的常见算法，matlab开发工具箱中的支持向量机，最小二乘回归分析算法，基于负熵最大的独立分量分析，供做算法研究人员参考，计算加权加速度,用MATLAB实现动态聚类或迭代自组织数据分析。- Using high-order cumulants of MPSK signal modulation recognition, Contains a common array signal processing algorithm, matlab
mfspskuq
- 利用贝叶斯原理估计混合logit模型的参数，包括主成分分析、因子分析、贝叶斯分析，大学数值分析算法，有循环检测，周期性检测，随机调制信号下的模拟ppm，最小二乘回归分析算法，表示出两帧图像间各个像素点的相对情况，采用加权网络中节点强度和权重都是幂率分布的模型。- Bayesian parameter estimation principle mixed logit model, Including principal component analysis, factor analysis, Ba
mycgymfa
- 采用加权网络中节点强度和权重都是幂率分布的模型，最小二乘回归分析算法，matlab程序运行时导入数据文件作为输入参数，有小波分析的盲信号处理，可以实现模式识别领域的数据的分类及回归，毕业设计有用。- Using weighted model nodes in the network strength and weight are power law distribution, Least-squares regression analysis algorithm, Import data fil
gouting
- 利用最小二乘算法实现对三维平面的拟合，采用加权网络中节点强度和权重都是幂率分布的模型，LCMV优化设计阵列处理信号。- Least-squares algorithm to fit a three-dimensional plane, Using weighted model nodes in the network strength and weight are power law distribution, LCMV optimization design array signal proc
IRLS
- 迭代重加权最小二乘算法，程序可以直接运行，并且给出了实例-Iterative reweighted least squares algorithm, the program can be run directly, and gives examples
sunjei
- 采用加权网络中节点强度和权重都是幂率分布的模型，最大似然（ML）准则和最大后验概率（MAP）准则，利用最小二乘算法实现对三维平面的拟合。- Using weighted model nodes in the network strength and weight are power law distribution, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Least-squares a
kaofiu_v59
- 利用最小二乘算法实现对三维平面的拟合，计算加权加速度,包括主成分分析、因子分析、贝叶斯分析。- Least-squares algorithm to fit a three-dimensional plane, Weighted acceleration, Including principal component analysis, factor analysis, Bayesian analysis.
wltsvm
- 加权最小二乘双支持向量机算法应用实例，作为学习双支持向量机的例子应用-Weighted least squares double support vector machine
IWLS
- 对最小二乘的参数进行重新加权，实现迁移学习并预测(Least-square importance weighted, transfer learning and prediction)