recognition

很好的一篇论文，内容讲解的很透彻啊，在我的工程项目中可是帮了大忙了(Very good paper, the content on a very thorough ah, in my project but of great help the)

说明：  SIMULATION A DC MACHINE WITH USING MATLAB

noise cancellation programs by lms and nlms

Feigenbaum this is development of matlab

用于计算射线声学声线,来找到所有声线中我想要的声线(to find the best acoustic line all )

一个EKF的简单应用,实现了用EKF算法对三维非线性系统进行仿真。(A simple application of EKF,I used the EKF algorithm to simulate a three-dimensional nonlinear system.)

利用matlab实现两幅图像之间的相似性度量，主要是基于颜色直方图(Between two images using matlab to achieve similarity measure is mainly based on color histogram)

GPS和INS组合导航程序，其中包括轨迹发生器、KALMAN滤波、模型建立、伪距伪距率组合方式进行仿真，可以对程序进行任意修改，有实验报告作为示例，可以作为导航专业的毕业设计参考例程使用。(Combination of GPS and INS navigation procedures, including trajectory generator, KALMAN filtering, modeling, pseudo-range pseudo-range rate of combination is simulated, the procedures can be freely modified, there are experimental report as an example, can serve as a navigation Graduation design reference routine use.)

unified power flow controller

Chapoly 通过求矩阵特征多项式的根来求其特征值. pmethod幂法求矩阵的主特征值及主特征向量. rpmethod瑞利商加速幂法求对称矩阵的主特征值及主特征向量. spmethod收缩法求矩阵全部特征值. ipmethod 收缩法求矩阵全部特征值 dimethod位移逆幂法求矩阵离某个常数最近的特征值及其对应的特征向量 qrtzQR基本算法求矩阵全部特征值. hessqrtz海森伯格QR算法求矩阵全部特征值. rqrtz瑞利商位移QR算法求矩阵全部特征值. (Chapoly characteristic polynomial by the root of a matrix to find the eigenvalues. Pmethod power method of a matrix eigenvalue and the principal eigenvectors. Rpmethod Rayleigh quotient accelerated power method Symmetric matrix eigenvalue and the principal eigenvectors. Spmethod contraction Law of the value of all the characteristics of a matrix. ipmethod contraction method the value of all the characteristics of a matrix inverse power law dimethod displacement from a constant of a matrix eigenvalue and its corresponding nearest feature vectors qrtzQR all the characteristics of the basic algorithm the value of a matrix. hessqrtz Heisenberg QR algorithm is the value of all the characteristics of a matrix. rqrtz Rayleigh quotient shift QR algorithm is the value of all the characteristics of a matrix.)