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Electronic Device modeling using matlab 2 ebooks

卡尔曼滤波扩展程序代码，很好的程序，大家都来下载吧！赶紧的！(Extended Kalman filtering code, very good program, we have to download it! Hurry it!)

本程序为EEMD分解程序，用于信号的EEMD分解(This procedure for the EEMD decomposition process, a signal for EEMD decomposition)

雷达数据处理对于观测的目标位置数据（称为点迹）进行滤波处理，自动形成航迹，并且可以对下一个目标的位置进行估计预测。利用最小二乘算法（LMS）进行滤波处理，得到了比较稳定的航迹估计。 最小二乘方法是参数估计中一种较为常见的参数估计方法。对于雷达观测数据，在我们假定已经精确知道航迹的运动学模型之后，通过建立观测方程，即可以对于模型的参数，如初速度，初始位置和加速度等进行最小均方误差估计。采用序贯最小二乘的方法可以对观测数据进行实时处理，已对待估计参数进行实时更新，然后利用观测模型可以对 数据进行滤波计算。(Radar data processing for target position data observed (known as trace points) filter processing, automatic track, and can be estimated to predict the position of the next target. Using the least squares algorithm (LMS) filtering process, have been relatively stable track estimates. Least-squares parameter estimation method is a more common parameter estimation method. For radar data, we assume that the kinematic model has been accurately track after, through the establishment of observation equations, which can be the parameters of the model, as ever speed, acceleration, etc. initial position and minimum mean square error estimation. Sequential least squares method using the observed data can be processed in real time, has been to treat the estimated parameters are updated in real time, and then use observational data can be filtered model calculations.)

对单元平均CFAR门限的求解进行了仿真，还分别求解了ＧＯＣＡ－ＣＦＡＲ以及ＳＯＣＡ－ＣＦＡＲ的门限(Average CFAR threshold for unit solving simulation, also were solved GOCA-CFAR and SOCA-CFAR threshold)

this code used for stephest algorithm

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)

finite difference time domain 3d code pec BC

说明：  从方程组中消去一些未知函数及其各阶导数，得到只含有一个未知函数的高阶常系数线性微分方程(Eliminated from the equations of some unknown function and its first derivative, the only unknown function contains a higher-order linear differential equations with constant coefficients)

Matlab中利用双线不变法设计椭圆数字滤波器(Digital filters using two-invariant method designed oval in Matlab)